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8,435,038 | 30 | 50 | 30. A non-transitory computer-readable medium comprising program code for causing a computer to perform a method, comprising: receiving, for each learner, a video feed generated by a camera at the learner's location, the video feed at least partially depicting both the learner and a subject on which the learner is demonstrating the practical skill; simultaneously displaying two or more of the video feeds for the plurality of learners at a location of the teacher; receiving and displaying one or more private questions to the teacher from one or more learners, the private questions not being conveyed to the other learners unless authorized by the teacher; and allowing the teacher to select one of the learners for individualized instruction by selecting an indication of the corresponding displayed private question; wherein the private questions can be submitted by one or more selected learners via a text message, an audio or a video; wherein the teacher responds to the one or more selected learners by a text message, audio or video by establishing a private video and/or audio communication channel between the teacher's computer system and the selected learner; wherein the teacher broadcasts the text, audio or video messages to a group of the selected learners by allowing the communication channel to be non-private for the group of selected learners to receive the instruction provided by the teacher; wherein allowing the teacher to store the video feed, annotating the stored video feed and selectively transmit the annotated stored video feed to one or more selected learners. | 30. A non-transitory computer-readable medium comprising program code for causing a computer to perform a method, comprising: receiving, for each learner, a video feed generated by a camera at the learner's location, the video feed at least partially depicting both the learner and a subject on which the learner is demonstrating the practical skill; simultaneously displaying two or more of the video feeds for the plurality of learners at a location of the teacher; receiving and displaying one or more private questions to the teacher from one or more learners, the private questions not being conveyed to the other learners unless authorized by the teacher; and allowing the teacher to select one of the learners for individualized instruction by selecting an indication of the corresponding displayed private question; wherein the private questions can be submitted by one or more selected learners via a text message, an audio or a video; wherein the teacher responds to the one or more selected learners by a text message, audio or video by establishing a private video and/or audio communication channel between the teacher's computer system and the selected learner; wherein the teacher broadcasts the text, audio or video messages to a group of the selected learners by allowing the communication channel to be non-private for the group of selected learners to receive the instruction provided by the teacher; wherein allowing the teacher to store the video feed, annotating the stored video feed and selectively transmit the annotated stored video feed to one or more selected learners. 50. The non-transitory computer-readable medium of claim 30 , further comprising program code for causing a computer to perform a method comprising: allowing the teacher to interactively establish communication with one or more of the learners by selecting their respective one or more video feeds from the display screen. | 0.678643 |
8,880,508 | 7 | 9 | 7. A computer-implemented method comprising: receiving a query for one or more data items stored in a database, wherein the query is associated with a query plan; determining whether to use at least one query operator that uses data having a format different from a storage model format of at least one of the data items stored in the database; and converting the format of the data used by the at least one query operator to another format that matches the storage model format of the at least one of the data items stored in the database, wherein the query plan is based on at least a syntax of the query and an order of clauses within the query, wherein a difference between the format of the data used by the at least one query operator and the storage model format of the at least one of the data items before conversion is one of the following: the format of the data used by the at least one query operator is a row-format and the storage model format of the at least one of the data items is a column-format; or the format of the data used by the at least one query operator is the column-format and the storage model of the at least one of the data items is the row-format, and wherein the receiving, the determining, and the converting are implemented on at least one processor. | 7. A computer-implemented method comprising: receiving a query for one or more data items stored in a database, wherein the query is associated with a query plan; determining whether to use at least one query operator that uses data having a format different from a storage model format of at least one of the data items stored in the database; and converting the format of the data used by the at least one query operator to another format that matches the storage model format of the at least one of the data items stored in the database, wherein the query plan is based on at least a syntax of the query and an order of clauses within the query, wherein a difference between the format of the data used by the at least one query operator and the storage model format of the at least one of the data items before conversion is one of the following: the format of the data used by the at least one query operator is a row-format and the storage model format of the at least one of the data items is a column-format; or the format of the data used by the at least one query operator is the column-format and the storage model of the at least one of the data items is the row-format, and wherein the receiving, the determining, and the converting are implemented on at least one processor. 9. The computer-implemented method of claim 7 , wherein the query plan is selected from a plurality of query plans for the query. | 0.8762 |
8,655,650 | 10 | 11 | 10. The method of claim 9 further comprises receiving two or more data streams having voice data encoded therein at a receiver, where each data stream corresponds to a channel in the system, and decoding each data stream into a set of speech coding parameters. | 10. The method of claim 9 further comprises receiving two or more data streams having voice data encoded therein at a receiver, where each data stream corresponds to a channel in the system, and decoding each data stream into a set of speech coding parameters. 11. The method of claim 10 wherein the voice data encoded in the data streams is encoded in accordance with mixed excitation linear prediction (MELP), such that speech coding parameters include gain, pitch, unvoiced flag, jitter, bandpass voicing and a line spectral frequency (LSF) vector. | 0.880952 |
9,836,290 | 9 | 13 | 9. A software execution process supporting dynamic behavior of a statically compiled computer program in a reduced runtime support environment, the process comprising the steps of: running at least a portion of the computer program in the reduced runtime support environment, the reduced size runtime functioning as a replacement for a larger runtime R, the reduced size runtime occupying less nonvolatile storage space than the larger runtime R as a result of containing less metadata than the larger runtime R, wherein metadata includes one or more of the following: a type name, a type member name, a type layout for garbage collection purposes, or a type member layout for garbage collection purposes; and utilizing at least one of the following dynamic support structures: a mapping between metadata and at least one native code runtime artifact; a mapping between runtime type descriptions, each runtime type description including at least one of the following: a list of implemented interfaces for a type which is in an execution scope of the compiled computer program, or a garbage collection layout for a type which is in an execution scope of the compiled computer program; or at least one piece of code which upon execution supports a reflection invocation of an artifact of the compiled computer program. | 9. A software execution process supporting dynamic behavior of a statically compiled computer program in a reduced runtime support environment, the process comprising the steps of: running at least a portion of the computer program in the reduced runtime support environment, the reduced size runtime functioning as a replacement for a larger runtime R, the reduced size runtime occupying less nonvolatile storage space than the larger runtime R as a result of containing less metadata than the larger runtime R, wherein metadata includes one or more of the following: a type name, a type member name, a type layout for garbage collection purposes, or a type member layout for garbage collection purposes; and utilizing at least one of the following dynamic support structures: a mapping between metadata and at least one native code runtime artifact; a mapping between runtime type descriptions, each runtime type description including at least one of the following: a list of implemented interfaces for a type which is in an execution scope of the compiled computer program, or a garbage collection layout for a type which is in an execution scope of the compiled computer program; or at least one piece of code which upon execution supports a reflection invocation of an artifact of the compiled computer program. 13. The process of claim 9 , wherein utilizing at least one piece of code which upon execution supports a reflection invocation comprises utilizing at least one of the following: a piece of code which performs a dynamically dispatched method call; a piece of code which performs a call-time bounds check; a piece of code which performs a calling convention conversion; or a piece of code which represents a compiler-intrinsic method that is inlined during compilation. | 0.684211 |
8,781,080 | 1 | 10 | 1. A method comprising: receiving an audio message from a first user; generating a text-based representation of the audio message; generating one or more identification tags using the text-based representation of the audio message, wherein at least one of the one or more identification tags includes a subject of the audio message; and presenting at least one of the text-based representation of the audio message or the one or more identification tags to a second user using a graphical user interface. | 1. A method comprising: receiving an audio message from a first user; generating a text-based representation of the audio message; generating one or more identification tags using the text-based representation of the audio message, wherein at least one of the one or more identification tags includes a subject of the audio message; and presenting at least one of the text-based representation of the audio message or the one or more identification tags to a second user using a graphical user interface. 10. The method of claim 1 , wherein the one or more identification tags includes a priority status tag, wherein the method further comprises prioritizing the text-based representation of the audio message presented to the second user with respect to other text-based representations of audio messages that are presented to the second user using the graphical user interface, and wherein the prioritization is based on the priority status tag associated with the text-based representation of the audio message and on other priority status tags associated with other text-based representations of audio messages. | 0.508065 |
8,340,405 | 15 | 16 | 15. The computer readable storage medium of claim 14 , wherein the one or more software modules further comprise instructions for: iteratively updating one or more of the weight values in response to subsequently receiving a digital file having one or more user provided annotations. | 15. The computer readable storage medium of claim 14 , wherein the one or more software modules further comprise instructions for: iteratively updating one or more of the weight values in response to subsequently receiving a digital file having one or more user provided annotations. 16. The computer readable storage medium of claim 15 , wherein the one or more software modules further comprise instructions for: generating a plurality of classifiers from the plurality of first features; applying the respective second digital file to the plurality of classifiers and determining a weight value corresponding to each of the plurality of classifiers; combining the weight values corresponding to one or more of the classifiers; and associating one or more annotations from a respective subset of matched files to the respective second digital file based on the combined weight values. | 0.882192 |
8,744,890 | 23 | 26 | 23. A non-transitory electronic storage media storing information related to recommending sales activities to individual workers based on worker specific information and overall company-level sales strategy, the stored information comprising: information related to one or more company goals, a plurality of products, a plurality of customers, and a plurality of workers; computer program instructions configured to cause a client computing platform to: determine a first configurable strategy based on a plurality of configurable market segments, wherein the first configurable strategy is related to promoting the first product; determine a first plurality of configurable workflows related to the first configurable strategy, the first plurality of configurable workflows comprising a first configurable workflow, wherein determining the first configurable workflow comprises determining a first set of activities related to promoting a first product to a first customer and a second configurable workflow, wherein determining the second configurable workflow comprises determining a second set of activities related to promoting the first product to a second customer; determine a first configurable market segment of the plurality of market segments, wherein determining the first configurable market segment comprises: receiving information related to the first customer to be targeted by the first configurable strategy; receiving information related to the first product to be targeted by the first configurable strategy; receiving abstraction information related to one or more of: a territory, a worker type, or a company goal, wherein the company goal comprises a sales goal for the first product; and defining the first configurable market segment based on the first customer, the first product, and the abstraction information; associate the first configurable workflow with the defined first configurable market segment to target the first product to the first customer to pursue the sales goal for the first product; determine a second configurable strategy based on a second plurality of market segments different from the first plurality of market segments, wherein the second configurable strategy is related to promoting a second product; and determine a second plurality of configurable workflows related to the second configurable strategy, the second plurality of configurable workflows comprising a third configurable workflow related to promoting a second product to the first customer; determine a first suggested activity for a first worker based on the first set of activities of the first workflow, the second set of activities of the second workflow, a first time period during which the first suggested activity is to be performed, a location associated with the first suggested activity, and a frequency of occurrence associated with the first suggested activity; determine a second suggested activity for the first worker responsive to a determination that the first worker is associated with the third workflow, wherein the second suggested activity is determined based on the first set of activities of the first configurable workflow, the second set of activities of the second configurable workflow, a third set of activities from the third configurable workflow, a second time period during which the second suggested activity is to be performed, a second location associated with the second suggested activity, and a second frequency of occurrence associated with the second suggested activity; output, to the first worker, a schedule for the first time period and the first suggested activity, wherein the schedule comprises a plurality of scheduled activities associated with the first worker within the first time period; and output, to the first worker, the second suggested activity with the schedule for the first time period and the first suggested activity. | 23. A non-transitory electronic storage media storing information related to recommending sales activities to individual workers based on worker specific information and overall company-level sales strategy, the stored information comprising: information related to one or more company goals, a plurality of products, a plurality of customers, and a plurality of workers; computer program instructions configured to cause a client computing platform to: determine a first configurable strategy based on a plurality of configurable market segments, wherein the first configurable strategy is related to promoting the first product; determine a first plurality of configurable workflows related to the first configurable strategy, the first plurality of configurable workflows comprising a first configurable workflow, wherein determining the first configurable workflow comprises determining a first set of activities related to promoting a first product to a first customer and a second configurable workflow, wherein determining the second configurable workflow comprises determining a second set of activities related to promoting the first product to a second customer; determine a first configurable market segment of the plurality of market segments, wherein determining the first configurable market segment comprises: receiving information related to the first customer to be targeted by the first configurable strategy; receiving information related to the first product to be targeted by the first configurable strategy; receiving abstraction information related to one or more of: a territory, a worker type, or a company goal, wherein the company goal comprises a sales goal for the first product; and defining the first configurable market segment based on the first customer, the first product, and the abstraction information; associate the first configurable workflow with the defined first configurable market segment to target the first product to the first customer to pursue the sales goal for the first product; determine a second configurable strategy based on a second plurality of market segments different from the first plurality of market segments, wherein the second configurable strategy is related to promoting a second product; and determine a second plurality of configurable workflows related to the second configurable strategy, the second plurality of configurable workflows comprising a third configurable workflow related to promoting a second product to the first customer; determine a first suggested activity for a first worker based on the first set of activities of the first workflow, the second set of activities of the second workflow, a first time period during which the first suggested activity is to be performed, a location associated with the first suggested activity, and a frequency of occurrence associated with the first suggested activity; determine a second suggested activity for the first worker responsive to a determination that the first worker is associated with the third workflow, wherein the second suggested activity is determined based on the first set of activities of the first configurable workflow, the second set of activities of the second configurable workflow, a third set of activities from the third configurable workflow, a second time period during which the second suggested activity is to be performed, a second location associated with the second suggested activity, and a second frequency of occurrence associated with the second suggested activity; output, to the first worker, a schedule for the first time period and the first suggested activity, wherein the schedule comprises a plurality of scheduled activities associated with the first worker within the first time period; and output, to the first worker, the second suggested activity with the schedule for the first time period and the first suggested activity. 26. The non-transitory electronic storage media of claim 23 , wherein the instructions are configured to cause the client computing platform to: access information related to a current location of the first worker; determine a first timed suggested activity to output to the first worker with the schedule based on: the schedule for the first worker; the first set of activities of the first configurable workflow; the second set of activities of the second configurable workflow; the current location of the first worker; and an activity value associated with performing the first timed suggested activity in the first time period, wherein the activity value is calculated based on one or more of: information relating to a schedule of a client associated with the first timed suggested activity, a wait time associated with the first timed suggested activity, travel time from the current location to a location of the first timed suggested activity, or an amount of time passed since an activity similar to the first timed suggested activity occurred, and output, to the first worker, the first timed suggested activity with the schedule. | 0.685155 |
8,706,739 | 1 | 3 | 1. A method for matching multiple user profiles from separate online social networks (OSNs), comprising: extracting target OSN user profile tokens from a target OSN user profile of a target user, wherein the target OSN user profile belongs to the target user in a first OSN of the plurality of OSNs, wherein extracting the target OSN user profile tokens from the target OSN user profile comprises: retrieving a target OSN user profile entry from the target OSN user profile; generating a target OSN user profile key token from the target OSN user profile entry based on a first sequence of alphanumeric characters in the target OSN user profile entry; and generating a target OSN user profile derived token from the target OSN user profile key token based on a first segment of the first sequence, wherein the first segment is delimited within the target OSN user profile entry using a set of pre-determined special characters, wherein the target OSN user profile tokens comprise the target OSN user profile key token and target OSN user profile derived token; extracting candidate OSN user profile tokens from a candidate OSN user profile of a candidate user, wherein the candidate OSN user profile belongs to the candidate user in a second OSN of the plurality of OSNs, wherein extracting the candidate OSN user profile tokens from the candidate OSN user profile comprises: retrieving a candidate OSN user profile entry from the candidate OSN user profile; generating a candidate OSN user profile key token from the candidate OSN user profile entry based on a second sequence of alphanumeric characters in the candidate OSN user profile entry; and generating a candidate OSN user profile derived token from the candidate OSN user profile key token based on a second segment of the second sequence, wherein the second segment is delimited within the candidate OSN user profile entry using the set of pre-determined special characters, wherein the candidate OSN user profile tokens comprise the candidate OSN user profile key token and candidate OSN user profile derived token; calculating, by the computer processor, a first similarity measure between the candidate OSN user profile and the target OSN user profile based on a first tally of a plurality of key tokens shared by the candidate OSN user profile tokens and the target OSN user profile tokens; calculating, by a computer processor, a second similarity measure between the candidate OSN user profile and the target OSN user profile based on a second tally of a plurality of derived tokens shared by the candidate OSN user profile tokens and the target OSN user profile tokens; aggregating, based on a pre-determined formula, the first similarity measure and the second similarity measure to generate a score; determining, in response to the score exceeding a pre-determined threshold, the target user and the candidate user as a single person; and combining, in response to at least the score exceeding the pre-determined threshold, the multiple user profiles from the separate OSNs for storing as an expanded profile of the single person, wherein the multiple user profiles comprise the target OSN user profile and the candidate OSN user profile, wherein the separate OSNs comprise the first OSN and the second OSN. | 1. A method for matching multiple user profiles from separate online social networks (OSNs), comprising: extracting target OSN user profile tokens from a target OSN user profile of a target user, wherein the target OSN user profile belongs to the target user in a first OSN of the plurality of OSNs, wherein extracting the target OSN user profile tokens from the target OSN user profile comprises: retrieving a target OSN user profile entry from the target OSN user profile; generating a target OSN user profile key token from the target OSN user profile entry based on a first sequence of alphanumeric characters in the target OSN user profile entry; and generating a target OSN user profile derived token from the target OSN user profile key token based on a first segment of the first sequence, wherein the first segment is delimited within the target OSN user profile entry using a set of pre-determined special characters, wherein the target OSN user profile tokens comprise the target OSN user profile key token and target OSN user profile derived token; extracting candidate OSN user profile tokens from a candidate OSN user profile of a candidate user, wherein the candidate OSN user profile belongs to the candidate user in a second OSN of the plurality of OSNs, wherein extracting the candidate OSN user profile tokens from the candidate OSN user profile comprises: retrieving a candidate OSN user profile entry from the candidate OSN user profile; generating a candidate OSN user profile key token from the candidate OSN user profile entry based on a second sequence of alphanumeric characters in the candidate OSN user profile entry; and generating a candidate OSN user profile derived token from the candidate OSN user profile key token based on a second segment of the second sequence, wherein the second segment is delimited within the candidate OSN user profile entry using the set of pre-determined special characters, wherein the candidate OSN user profile tokens comprise the candidate OSN user profile key token and candidate OSN user profile derived token; calculating, by the computer processor, a first similarity measure between the candidate OSN user profile and the target OSN user profile based on a first tally of a plurality of key tokens shared by the candidate OSN user profile tokens and the target OSN user profile tokens; calculating, by a computer processor, a second similarity measure between the candidate OSN user profile and the target OSN user profile based on a second tally of a plurality of derived tokens shared by the candidate OSN user profile tokens and the target OSN user profile tokens; aggregating, based on a pre-determined formula, the first similarity measure and the second similarity measure to generate a score; determining, in response to the score exceeding a pre-determined threshold, the target user and the candidate user as a single person; and combining, in response to at least the score exceeding the pre-determined threshold, the multiple user profiles from the separate OSNs for storing as an expanded profile of the single person, wherein the multiple user profiles comprise the target OSN user profile and the candidate OSN user profile, wherein the separate OSNs comprise the first OSN and the second OSN. 3. The method of claim 1 , further comprising: selectively augmenting the target OSN user profile tokens with a semantically equivalent addition; and storing the target OSN user profile tokens with the semantically equivalent addition in a data structure that is partitioned based on the plurality of users. | 0.676842 |
8,095,355 | 17 | 18 | 17. A computer readable medium storing instructions that upon execution by a processing device cause the processing device to perform operations, comprising: receiving, using one or more processors, a user request to translate a source web document at a location from a first language text to a second language text, the request including a uniform resource locator corresponding to the source web document; generating a translated web document containing a translation of the source web document into the second language text; presenting the translated web document to the user; and displaying the first language text that corresponds to a portion of the translated web document in a graphical element overlaying the translated web document in response to the user pointing to the portion of the translated web document. | 17. A computer readable medium storing instructions that upon execution by a processing device cause the processing device to perform operations, comprising: receiving, using one or more processors, a user request to translate a source web document at a location from a first language text to a second language text, the request including a uniform resource locator corresponding to the source web document; generating a translated web document containing a translation of the source web document into the second language text; presenting the translated web document to the user; and displaying the first language text that corresponds to a portion of the translated web document in a graphical element overlaying the translated web document in response to the user pointing to the portion of the translated web document. 18. The computer readable medium of claim 17 , further including instructions that upon execution cause the processing device to perform operations comprising: displaying the first language text after a predetermined period of time has elapsed after the user points to the portion of the translated document; removing the display of the first language text after a second predetermined period of time has elapsed after a user ceases to point to the portion of the translated document; and canceling the removal the display of the first language text if the user again points to the portion of the translated document before the second predetermined period of time has elapsed. | 0.500739 |
9,412,392 | 24 | 35 | 24. A electronic device configured to process voice commands, comprising: one or more input devices; a non-transitory computer-readable storage medium comprising computer instructions for: in response to user input at the one or more input devices, recording at least a portion of a voice command on the electronic device; storing contextual information of the electronic device when the electronic device is recording the at least a portion of the voice command; and after recording the at least a portion of the voice command and storing the contextual information of the electronic device, uploading the at least a portion of the recorded voice command and the stored contextual information from the electronic device to a remote computing equipment; and one or more processors capable of executing the computer instructions. | 24. A electronic device configured to process voice commands, comprising: one or more input devices; a non-transitory computer-readable storage medium comprising computer instructions for: in response to user input at the one or more input devices, recording at least a portion of a voice command on the electronic device; storing contextual information of the electronic device when the electronic device is recording the at least a portion of the voice command; and after recording the at least a portion of the voice command and storing the contextual information of the electronic device, uploading the at least a portion of the recorded voice command and the stored contextual information from the electronic device to a remote computing equipment; and one or more processors capable of executing the computer instructions. 35. The electronic device of claim 24 , wherein the contextual information comprises a date and time that the electronic device is recording the at least a portion of the voice command. | 0.781324 |
9,836,458 | 8 | 10 | 8. A computer program product for enabling attendees of a web conference to view materials of the web conference in their native language, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code comprising the programming instructions for: receiving a request from an attendee to join said web conference; detecting a native language type of said attendee; creating a virtual environment that is a clone of a host environment of a presenter of said web conference that runs a native language pack of a preferred native language of said attendee based on said detected native language type of said attendee or a language preference indicated by said attendee in response to said preferred native language of said attendee being different from a preferred native language of said presenter, wherein said native language pack of said preferred native language of said attendee translates an operating system and an application user interface of said host environment into said preferred native language of said attendee; capturing a shared screen shot of a screen from said host environment of said presenter of said web conference; translating said captured shared screen shot into said preferred native language of said attendee using said native language pack of said preferred native language of said attendee; and sending said translated captured shared sheen shot in said preferred native language of said attendee to said attendee from said virtual environment. | 8. A computer program product for enabling attendees of a web conference to view materials of the web conference in their native language, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code comprising the programming instructions for: receiving a request from an attendee to join said web conference; detecting a native language type of said attendee; creating a virtual environment that is a clone of a host environment of a presenter of said web conference that runs a native language pack of a preferred native language of said attendee based on said detected native language type of said attendee or a language preference indicated by said attendee in response to said preferred native language of said attendee being different from a preferred native language of said presenter, wherein said native language pack of said preferred native language of said attendee translates an operating system and an application user interface of said host environment into said preferred native language of said attendee; capturing a shared screen shot of a screen from said host environment of said presenter of said web conference; translating said captured shared screen shot into said preferred native language of said attendee using said native language pack of said preferred native language of said attendee; and sending said translated captured shared sheen shot in said preferred native language of said attendee to said attendee from said virtual environment. 10. The computer program product as recited in claim 8 , wherein the program code further comprises the programming instructions for: capturing an action along with generated dynamic content and associated metadata in response to said presenter performing said action on said screen of said host environment. | 0.501618 |
9,152,537 | 1 | 10 | 1. A method, comprising: recording, into a first node, a mapping of a current stack trace in response to an execution of a first instruction to construct a first element of a plurality of elements in a computer program, wherein the current stack trace is a stack trace that includes stack frames generated up to a particular point in the execution of code instructions in the computer program; storing the first node in a data structure configured for storing a plurality of nodes, wherein the first node includes a first set of stack frames associated with the execution of the first instruction to construct the first element; incrementally updating the first node by recording, into the first node, a first updated mapping of the current stack trace in response to the execution of a first subsequent instruction that has the first element as a parameter; recording, into a second node, the mapping of the current stack trace in response to the execution of a second instruction to construct a second element of the plurality of elements in the computer program; storing the second node in the data structure, wherein the second node comprises: a portion of the mapping of the current stack trace, the portion of the mapping of the current stack trace including a second set of stack frames associated with the execution of the second instruction to construct the second element; and a pointer to the first node; incrementally updating the second node by recording, into the second node, a second updated mapping of the current stack trace in response to the execution of a second subsequent instruction that has the second element as the parameter; and in response to a determination that no additional instruction for constructing an element exists in the computer program, generating a node string from the plurality of nodes that includes at least the first node and the second node. | 1. A method, comprising: recording, into a first node, a mapping of a current stack trace in response to an execution of a first instruction to construct a first element of a plurality of elements in a computer program, wherein the current stack trace is a stack trace that includes stack frames generated up to a particular point in the execution of code instructions in the computer program; storing the first node in a data structure configured for storing a plurality of nodes, wherein the first node includes a first set of stack frames associated with the execution of the first instruction to construct the first element; incrementally updating the first node by recording, into the first node, a first updated mapping of the current stack trace in response to the execution of a first subsequent instruction that has the first element as a parameter; recording, into a second node, the mapping of the current stack trace in response to the execution of a second instruction to construct a second element of the plurality of elements in the computer program; storing the second node in the data structure, wherein the second node comprises: a portion of the mapping of the current stack trace, the portion of the mapping of the current stack trace including a second set of stack frames associated with the execution of the second instruction to construct the second element; and a pointer to the first node; incrementally updating the second node by recording, into the second node, a second updated mapping of the current stack trace in response to the execution of a second subsequent instruction that has the second element as the parameter; and in response to a determination that no additional instruction for constructing an element exists in the computer program, generating a node string from the plurality of nodes that includes at least the first node and the second node. 10. The method of claim 1 , wherein the second subsequent instruction comprises a fetching of data associated with the second element. | 0.95152 |
8,229,927 | 1 | 2 | 1. An information search apparatus, comprising: an interface configured to obtain a search option input by a user; a processor; and a storage device configured to store a plurality of instructions which causes the processor to perform searching when the search option is obtained through the interface, wherein the processor is further configured to: determine a search term based on the search option, the search term including an extracted search term that is extracted from the search option; search a document database to obtain a document that matches the search term; generate a search result including document information identifying the document that matches the search term and relevancy information indicating a degree of relevancy between the search term and the document; cause a display device to display the search result in a format indicating the correspondence relationship of the document information, the search term, and the relevancy information, wherein the format indicating the correspondence relationship is a matrix, the matrix including a cell that represents relevancy information between the search term and the document, the matrix is displayed on the display device, and the cell, which is linked to the document, is configured to be activated by a user input and to cause the display device to display at least a portion of the document having the search term with the search term displayed in the document differently from other words in the document, wherein the matrix includes a row including a matrix element representing one of the search term or the document information, a column including a matrix element representing another one of the search term or the document information, and the cell being provided at a location where the matrix element representing the search term and the matrix element representing the document information meet and indicating the degree of relevancy between the search term represented by the corresponding matrix element and the document identified by the document information represented by the corresponding matrix element, and wherein, when the search term includes a plurality of search terms, the processor is further configured to generate a plurality of search results for each one of the plurality of search terms, and cause the display device to display the plurality of search results in the format indicating the correspondence relationship of the document information, the search term, and the relevancy information for each one of the plurality of search results; and the relevancy information is displayed visually in a graphical image having a shape representing the relevancy information. | 1. An information search apparatus, comprising: an interface configured to obtain a search option input by a user; a processor; and a storage device configured to store a plurality of instructions which causes the processor to perform searching when the search option is obtained through the interface, wherein the processor is further configured to: determine a search term based on the search option, the search term including an extracted search term that is extracted from the search option; search a document database to obtain a document that matches the search term; generate a search result including document information identifying the document that matches the search term and relevancy information indicating a degree of relevancy between the search term and the document; cause a display device to display the search result in a format indicating the correspondence relationship of the document information, the search term, and the relevancy information, wherein the format indicating the correspondence relationship is a matrix, the matrix including a cell that represents relevancy information between the search term and the document, the matrix is displayed on the display device, and the cell, which is linked to the document, is configured to be activated by a user input and to cause the display device to display at least a portion of the document having the search term with the search term displayed in the document differently from other words in the document, wherein the matrix includes a row including a matrix element representing one of the search term or the document information, a column including a matrix element representing another one of the search term or the document information, and the cell being provided at a location where the matrix element representing the search term and the matrix element representing the document information meet and indicating the degree of relevancy between the search term represented by the corresponding matrix element and the document identified by the document information represented by the corresponding matrix element, and wherein, when the search term includes a plurality of search terms, the processor is further configured to generate a plurality of search results for each one of the plurality of search terms, and cause the display device to display the plurality of search results in the format indicating the correspondence relationship of the document information, the search term, and the relevancy information for each one of the plurality of search results; and the relevancy information is displayed visually in a graphical image having a shape representing the relevancy information. 2. The apparatus of claim 1 , wherein, when the document that matches the search term includes a plurality of documents, the processor is further configured to: generate, for each one of the plurality of documents, search result correspondence relationship information indicating the correspondence relationship of at least two of the document information, the search term, and the relevancy information, wherein the cell representing the relevancy information includes the search result correspondence relationship information. | 0.6 |
9,583,106 | 1 | 6 | 1. A method for presenting interactive audio content, the method comprising: receiving, using a computing device that includes a hardware processor, an audio input device, and an audio output device, an interactive audiobook having narrative content that includes a plurality of action points, wherein each of the plurality of action points provides a plurality of user actions and a narrative portion corresponding to each of the plurality of user actions; receiving, using the hardware processor of the computing device, a selection of a user engagement density from a user, wherein the selection determines a number of the plurality of action points in the narrative content of the interactive audiobook, and wherein a higher-selected user engagement density increases the number of the plurality of action points and a lower-selected user engagement density decreases the number of action points in the narrative content; causing, using the hardware processor of the computing device, the narrative content with the determined number of the plurality of action points to be presented via the audio output device to the user based on the selected user engagement density; determining, using the hardware processor of the computing device, that a speech input has been received by the audio input device at one of the plurality of action points during the playback of the narrative content of the interactive audiobook; converting, using the hardware processor of the computing device, the speech input to a text input; determining, using the hardware processor of the computing device, whether the user action associated with the text input corresponds to one of the plurality of user actions; selecting, using the hardware processor of the computing device, the narrative portion corresponding to the text input in response to determining that the user action corresponds to one of the plurality of user actions; converting, using the hardware processor of the computing device, the selected narrative portion to an audio output; modifying, using the hardware processor of the computing device, the narrative content of the interactive audiobook with the converted audio output of the selected narrative portion; and causing, using the hardware processor of the computing device, the narrative content with the converted audio output of the selected narrative portion to be presented to the user via the audio output device. | 1. A method for presenting interactive audio content, the method comprising: receiving, using a computing device that includes a hardware processor, an audio input device, and an audio output device, an interactive audiobook having narrative content that includes a plurality of action points, wherein each of the plurality of action points provides a plurality of user actions and a narrative portion corresponding to each of the plurality of user actions; receiving, using the hardware processor of the computing device, a selection of a user engagement density from a user, wherein the selection determines a number of the plurality of action points in the narrative content of the interactive audiobook, and wherein a higher-selected user engagement density increases the number of the plurality of action points and a lower-selected user engagement density decreases the number of action points in the narrative content; causing, using the hardware processor of the computing device, the narrative content with the determined number of the plurality of action points to be presented via the audio output device to the user based on the selected user engagement density; determining, using the hardware processor of the computing device, that a speech input has been received by the audio input device at one of the plurality of action points during the playback of the narrative content of the interactive audiobook; converting, using the hardware processor of the computing device, the speech input to a text input; determining, using the hardware processor of the computing device, whether the user action associated with the text input corresponds to one of the plurality of user actions; selecting, using the hardware processor of the computing device, the narrative portion corresponding to the text input in response to determining that the user action corresponds to one of the plurality of user actions; converting, using the hardware processor of the computing device, the selected narrative portion to an audio output; modifying, using the hardware processor of the computing device, the narrative content of the interactive audiobook with the converted audio output of the selected narrative portion; and causing, using the hardware processor of the computing device, the narrative content with the converted audio output of the selected narrative portion to be presented to the user via the audio output device. 6. The method of claim 1 , wherein determining the user engagement density is based on the speech input received at each of the plurality of action points. | 0.706439 |
8,386,232 | 8 | 24 | 8. The method of claim 1 , wherein the step of generating clusters of related items comprises associating a particular item to more than one of the clusters. | 8. The method of claim 1 , wherein the step of generating clusters of related items comprises associating a particular item to more than one of the clusters. 24. One or more non-transitory computer readable storage media storing instructions which, when executed by one or more computing devices, cause performance of the method recited in claim 8 . | 0.936629 |
10,002,613 | 21 | 28 | 21. A computer-implemented method comprising: receiving, using a microphone of a computing device, a request to designate a particular candidate hotword that is not currently designated as a hotword, as a hotword; determining that the particular candidate hotword satisfies one or more hotword suitability criteria; in response to determining that the particular candidate hotword satisfies one or more hotword suitability criteria, designating the particular candidate hotword as a custom hotword; after designating the particular candidate hotword as a custom hotword, determining that subsequently received audio data received using the microphone of the computing device includes sounds that are characteristic of an utterance of the custom hotword; in response to determining that the subsequently received audio data includes sounds that are characteristic of an utterance of the custom hotword: providing, on a display of the computing device or using a speaker of the computing device, an indication that the custom hotword was detected; and causing the computing device to enter a ready state for receiving and processing voice commands uttered after the utterance of the custom hotword. | 21. A computer-implemented method comprising: receiving, using a microphone of a computing device, a request to designate a particular candidate hotword that is not currently designated as a hotword, as a hotword; determining that the particular candidate hotword satisfies one or more hotword suitability criteria; in response to determining that the particular candidate hotword satisfies one or more hotword suitability criteria, designating the particular candidate hotword as a custom hotword; after designating the particular candidate hotword as a custom hotword, determining that subsequently received audio data received using the microphone of the computing device includes sounds that are characteristic of an utterance of the custom hotword; in response to determining that the subsequently received audio data includes sounds that are characteristic of an utterance of the custom hotword: providing, on a display of the computing device or using a speaker of the computing device, an indication that the custom hotword was detected; and causing the computing device to enter a ready state for receiving and processing voice commands uttered after the utterance of the custom hotword. 28. The computer-implemented method of claim 21 , comprising: in response to determining that subsequently received audio data includes sounds that are characteristic of an utterance of the custom hotword, providing one or more commands for waking up the computing device. | 0.896104 |
8,140,330 | 16 | 17 | 16. A system for detecting repeated patterns in a dialog system, comprising: a speech recognizer hardware component receiving an initial utterance from a user in the dialog sequence as a set of test patterns, and receiving a correction utterance from the user in response to an output from a response generator of the dialog system, wherein the initial utterance includes a first plurality of words in a first order and the correction utterance includes a second plurality of words in a second order, wherein at least some of the second plurality of words are repeated from the first plurality of words; an event detector hardware component detecting the occurrence of repeated segments between the initial utterance and the correction utterance; a segmentation hardware component segmenting the correction utterance into a set of reference patterns by identifying silence regions separating each of the first plurality of words within the initial utterance; a feature extraction hardware component extracting feature vectors from the test patterns and the reference patterns; and a pattern comparison component of the event detector comparing each test pattern with each reference pattern over the entire length of the set of test patterns and the set of reference patterns, using a dynamic time warping process in order to determine boundaries of the reference and test patterns using spectral characteristics of the initial and correction utterances, and computing distance scores between each reference pattern and each test pattern to identify test patterns with a distance score of less than a defined distance threshold as a repeated pattern. | 16. A system for detecting repeated patterns in a dialog system, comprising: a speech recognizer hardware component receiving an initial utterance from a user in the dialog sequence as a set of test patterns, and receiving a correction utterance from the user in response to an output from a response generator of the dialog system, wherein the initial utterance includes a first plurality of words in a first order and the correction utterance includes a second plurality of words in a second order, wherein at least some of the second plurality of words are repeated from the first plurality of words; an event detector hardware component detecting the occurrence of repeated segments between the initial utterance and the correction utterance; a segmentation hardware component segmenting the correction utterance into a set of reference patterns by identifying silence regions separating each of the first plurality of words within the initial utterance; a feature extraction hardware component extracting feature vectors from the test patterns and the reference patterns; and a pattern comparison component of the event detector comparing each test pattern with each reference pattern over the entire length of the set of test patterns and the set of reference patterns, using a dynamic time warping process in order to determine boundaries of the reference and test patterns using spectral characteristics of the initial and correction utterances, and computing distance scores between each reference pattern and each test pattern to identify test patterns with a distance score of less than a defined distance threshold as a repeated pattern. 17. The system of claim 16 further comprising a decision rule hardware component defining the distance threshold. | 0.504386 |
6,167,393 | 12 | 13 | 12. The apparatus of claim 1, wherein the query engine is programmed to evaluate an operator having a multi-valued operand, having one or more values corresponding thereto and arising from a single record. | 12. The apparatus of claim 1, wherein the query engine is programmed to evaluate an operator having a multi-valued operand, having one or more values corresponding thereto and arising from a single record. 13. The apparatus of claim 12, wherein the operator is selected from the group consisting of logical operators, comparison operators, quantifier operators, aggregator operators, selector operators, field existence operators, and arithmetic operators. | 0.86688 |
8,825,486 | 15 | 20 | 15. A method for generating speech output via a speech-enabled application, the method comprising: generating, using at least one computer system executing the speech-enabled application, a plurality of text strings, each of the plurality of text strings corresponding to a portion of a desired speech output; inputting the plurality of text strings to at least one software module configured to identify a first portion of a first text string of the plurality of text strings as differing from a corresponding first portion of a second text string of the plurality of text strings, and a second portion of the first text string as not differing from a corresponding second portion of the second text string; receiving, from the at least one software module, speech synthesis output to render the plurality of text strings with contrastive stress assigned to the first portion of the first text string and/or to the corresponding first portion of the second text string, but not to the second portion of the first text string, and not to the corresponding second portion of the second text string; and generating, using the speech synthesis output, an audio speech output corresponding to the desired speech output. | 15. A method for generating speech output via a speech-enabled application, the method comprising: generating, using at least one computer system executing the speech-enabled application, a plurality of text strings, each of the plurality of text strings corresponding to a portion of a desired speech output; inputting the plurality of text strings to at least one software module configured to identify a first portion of a first text string of the plurality of text strings as differing from a corresponding first portion of a second text string of the plurality of text strings, and a second portion of the first text string as not differing from a corresponding second portion of the second text string; receiving, from the at least one software module, speech synthesis output to render the plurality of text strings with contrastive stress assigned to the first portion of the first text string and/or to the corresponding first portion of the second text string, but not to the second portion of the first text string, and not to the corresponding second portion of the second text string; and generating, using the speech synthesis output, an audio speech output corresponding to the desired speech output. 20. The method of claim 15 , wherein the speech synthesis output comprises identification of a plurality of audio recordings to render the plurality of text strings as speech, at least one of the plurality of audio recordings being selected to render the first portion of the first text string and/or the first portion of the second text string as speech carrying contrastive stress. | 0.501302 |
9,003,361 | 19 | 20 | 19. The system of claim 14 , wherein creating the plurality of methods argument for the plurality of URIs comprises: identifying a template that corresponds to the identified programming language; identifying RESTful (Representational State Transfer) service description language describing the plurality of URIs; and populating the template with input data extracted from the RESTful service description language describing the corresponding URI, wherein the populated template represents the method argument for the corresponding URI. | 19. The system of claim 14 , wherein creating the plurality of methods argument for the plurality of URIs comprises: identifying a template that corresponds to the identified programming language; identifying RESTful (Representational State Transfer) service description language describing the plurality of URIs; and populating the template with input data extracted from the RESTful service description language describing the corresponding URI, wherein the populated template represents the method argument for the corresponding URI. 20. The system of claim 19 , wherein populating the template comprises: populating the template with at least one of URI HTTP attribute metadata, HTTP method metadata, header metadata, body argument metadata, URI argument metadata, or response argument metadata. | 0.850114 |
9,317,767 | 1 | 8 | 1. A computer-implemented method for selecting at least one segmentation parameter for optical character recognition comprising: receiving, using one or more computing devices, an image having a character string that includes one or more characters; receiving, using the one or more computing devices, a character string identifying each of the one or more characters; automatically generating, using the one or more computing devices, at least one segmentation parameter; performing segmentation, using the one or more computing devices, on the image having the character string using the at least one segmentation parameter, wherein segmentation is configured to separate each character of the character string; determining, using the one or more computing devices, if a resultant segmentation satisfies an ASCII uniformity criteria; and if the resultant segmentation satisfies the ASCII uniformity criteria, selecting the at least one segmentation parameter. | 1. A computer-implemented method for selecting at least one segmentation parameter for optical character recognition comprising: receiving, using one or more computing devices, an image having a character string that includes one or more characters; receiving, using the one or more computing devices, a character string identifying each of the one or more characters; automatically generating, using the one or more computing devices, at least one segmentation parameter; performing segmentation, using the one or more computing devices, on the image having the character string using the at least one segmentation parameter, wherein segmentation is configured to separate each character of the character string; determining, using the one or more computing devices, if a resultant segmentation satisfies an ASCII uniformity criteria; and if the resultant segmentation satisfies the ASCII uniformity criteria, selecting the at least one segmentation parameter. 8. The computer-implemented method of claim 1 , wherein the at least one segmentation parameter includes one or more of polarity, line refinement, angle search range, skew search range, normalization mode, stroke width, binarization threshold, border fragments, pixel count, fragment contrast threshold, character height, character width, intercharacter gap, intracharacter gap, fragment distance to main line, fragment merge mode, minimum character aspect, character width type, analysis mode, pitch metric, pitch type, minimum pitch, space insertion, width of space character. | 0.564103 |
8,762,469 | 20 | 21 | 20. A method for operating an automated assistant, comprising: at a server computer system provided by a first entity, the server computer system comprising a processor and memory storing instructions for execution by the processor: receiving a voice command and contextual information from the portable electronic device; processing the voice command, using a speech recognition service provided by a second entity different from the first entity, to generate a text string from the voice command; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device. | 20. A method for operating an automated assistant, comprising: at a server computer system provided by a first entity, the server computer system comprising a processor and memory storing instructions for execution by the processor: receiving a voice command and contextual information from the portable electronic device; processing the voice command, using a speech recognition service provided by a second entity different from the first entity, to generate a text string from the voice command; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device. 21. The method of claim 20 , wherein the results associated with processing the text string are displayed at the portable electronic device. | 0.834906 |
8,897,151 | 1 | 2 | 1. A computer-implemented system for application protocol field extraction, comprising: an extraction specification that specifies data elements to be extracted from data packets and is expressed in terms of a context-free grammar, where the grammar defines grammatical structures of data packets transmitted in accordance with an application protocol and is defined as a tuple having nonterminals, terminals, counters, production rules and a start nonterminal, such that the counters are variables with an integer value used to chronicle parsing history of the production rules, and at least one of the production rules includes an action association with a terminal or nonterminal comprising body of the production rule and the action is an expression for updating a value of a counter defined by the grammar; an automata generator configured to receive the extraction specification and generate a counting automaton; and a field extractor configured to receive a data flow comprised of a plurality of data packets traversing through a network and extract data elements from the data packets in accordance with the counting automaton, where the field extractor is implemented by an integrated circuit. | 1. A computer-implemented system for application protocol field extraction, comprising: an extraction specification that specifies data elements to be extracted from data packets and is expressed in terms of a context-free grammar, where the grammar defines grammatical structures of data packets transmitted in accordance with an application protocol and is defined as a tuple having nonterminals, terminals, counters, production rules and a start nonterminal, such that the counters are variables with an integer value used to chronicle parsing history of the production rules, and at least one of the production rules includes an action association with a terminal or nonterminal comprising body of the production rule and the action is an expression for updating a value of a counter defined by the grammar; an automata generator configured to receive the extraction specification and generate a counting automaton; and a field extractor configured to receive a data flow comprised of a plurality of data packets traversing through a network and extract data elements from the data packets in accordance with the counting automaton, where the field extractor is implemented by an integrated circuit. 2. The system of claim 1 wherein the production rules are in the form of <predicate>: <nonterminal>→<body>, such that the body is an ordered sequence of terminals and nonterminals and each predicate is expressed in terms of at least one counter. | 0.832879 |
9,311,363 | 1 | 6 | 1. A method performed by data processing apparatus, the method comprising: obtaining, for a product or service, quality feedback including multiple different quality scores representing different measures of quality that have been assigned to the product or service by multiple different users, the quality feedback including feedback text submitted by the multiple different users with the quality scores; identifying, from the feedback text, a characteristic, of the product or service, that has been referenced in the feedback text submitted by the multiple different users; determining, by a data processing apparatus, an amount of influence of the characteristic on the quality scores that were submitted with the feedback text based on a difference between a first aggregate value of the quality scores that were submitted without feedback text identifying the characteristic relative to a second aggregate value of the quality scores that were submitted with feedback text identifying the characteristic, wherein the amount of influence corresponds to differences in quality scores that are attributable to the characteristic; identifying, for a given user, a quality profile specifying a characteristic weight that is a measure of importance of the characteristic to the given user; determining, by a data processing apparatus and for the given user, a personalized estimated quality value for the product or service, including adjusting an overall quality score for the product or service based on the influence of the characteristic on the quality scores based on the characteristic weight for the given user; and ranking, by a data processing apparatus and for the given user, the product or service among other products or services based on the personalized estimated quality score. | 1. A method performed by data processing apparatus, the method comprising: obtaining, for a product or service, quality feedback including multiple different quality scores representing different measures of quality that have been assigned to the product or service by multiple different users, the quality feedback including feedback text submitted by the multiple different users with the quality scores; identifying, from the feedback text, a characteristic, of the product or service, that has been referenced in the feedback text submitted by the multiple different users; determining, by a data processing apparatus, an amount of influence of the characteristic on the quality scores that were submitted with the feedback text based on a difference between a first aggregate value of the quality scores that were submitted without feedback text identifying the characteristic relative to a second aggregate value of the quality scores that were submitted with feedback text identifying the characteristic, wherein the amount of influence corresponds to differences in quality scores that are attributable to the characteristic; identifying, for a given user, a quality profile specifying a characteristic weight that is a measure of importance of the characteristic to the given user; determining, by a data processing apparatus and for the given user, a personalized estimated quality value for the product or service, including adjusting an overall quality score for the product or service based on the influence of the characteristic on the quality scores based on the characteristic weight for the given user; and ranking, by a data processing apparatus and for the given user, the product or service among other products or services based on the personalized estimated quality score. 6. The method of claim 1 , wherein determining, for the given user, a personalized estimated quality score for the product or service based on the influence of the characteristic on the quality scores and the characteristic weight for the given user comprises: determining that the characteristic weight for the given user indicates that the characteristic is important to the given user; determining that the influence of the characteristic on the quality scores is a positive influence; and increasing a baseline quality score for the product or service based, at least in part, on a magnitude of the positive influence. | 0.697176 |
6,026,410 | 24 | 25 | 24. The method of claim 21, further comprising: generating a shadowbox associated with the input text, the shadowbox including the associated information associated with the keywords with the input text. | 24. The method of claim 21, further comprising: generating a shadowbox associated with the input text, the shadowbox including the associated information associated with the keywords with the input text. 25. The method of claim 24, further comprising: identifying the type of the input text received, the type comprising one or more of the following: a to do list, an appointment, a reminder, a calendar entry, an FYI, an action item, or an electronic mail message. | 0.816197 |
7,533,362 | 12 | 19 | 12. A computer system, comprising: an input interface operable to parse a high-level language program, the high-level language program configured to run on a conventional central processing unit, wherein the input interface is operable to identify a hardware resource count included in the high-level language program, wherein the hardware resource count is associated with a code sequence in the high-level language program; a processor operable to generate hardware acceleration logic for implementing the code sequence using the hardware resource count, wherein the hardware resource count specifies the number of resources to use to implement the code sequence on a programmable chip. | 12. A computer system, comprising: an input interface operable to parse a high-level language program, the high-level language program configured to run on a conventional central processing unit, wherein the input interface is operable to identify a hardware resource count included in the high-level language program, wherein the hardware resource count is associated with a code sequence in the high-level language program; a processor operable to generate hardware acceleration logic for implementing the code sequence using the hardware resource count, wherein the hardware resource count specifies the number of resources to use to implement the code sequence on a programmable chip. 19. The computer system of claim 12 , wherein the central processing unit is a general purpose processor. | 0.723684 |
9,066,049 | 15 | 19 | 15. A system comprising: one or more processors; and memory, communicatively coupled to the one or more processors, storing a component configured to: extract script words indicative of dialogue words from provided script data; obtain timecodes included in recorded dialogue audio data corresponding to at least a portion of the script words, the timecodes associated with recorded audio dialogue words; match one or more script words to one or more recorded audio dialogue words, the matching comprising merging an N-gram of the script data to an N-gram of the recorded dialogue audio data; determine hard and soft alignment points based, at least in part, on the matching, the hard alignment point being indicative of a point at which the one or more recorded audio dialogue words match to the one or more script words and the soft alignment point being indicative of a point at which the one or more recorded audio dialogue words partially match to the one or more script words; define boundaries of a sub-matrix using the hard alignment point, the sub-matrix including a block of text corresponding to the one or more recorded audio dialogue words matched to the one or more script words; generate time-aligned script data that includes the script words and their corresponding timecodes based, at least in part, on the sub-matrix; and include at least one recorded audio dialogue word in the time-aligned script data in place of a corresponding script word responsive to determining that a confidence level of the at least one recorded audio dialogue word is greater than a confidence level of the corresponding script word. | 15. A system comprising: one or more processors; and memory, communicatively coupled to the one or more processors, storing a component configured to: extract script words indicative of dialogue words from provided script data; obtain timecodes included in recorded dialogue audio data corresponding to at least a portion of the script words, the timecodes associated with recorded audio dialogue words; match one or more script words to one or more recorded audio dialogue words, the matching comprising merging an N-gram of the script data to an N-gram of the recorded dialogue audio data; determine hard and soft alignment points based, at least in part, on the matching, the hard alignment point being indicative of a point at which the one or more recorded audio dialogue words match to the one or more script words and the soft alignment point being indicative of a point at which the one or more recorded audio dialogue words partially match to the one or more script words; define boundaries of a sub-matrix using the hard alignment point, the sub-matrix including a block of text corresponding to the one or more recorded audio dialogue words matched to the one or more script words; generate time-aligned script data that includes the script words and their corresponding timecodes based, at least in part, on the sub-matrix; and include at least one recorded audio dialogue word in the time-aligned script data in place of a corresponding script word responsive to determining that a confidence level of the at least one recorded audio dialogue word is greater than a confidence level of the corresponding script word. 19. The system of claim 15 , wherein the hard alignment point and the soft alignment point are processed to generate the time-aligned script data. | 0.731618 |
8,230,329 | 6 | 7 | 6. The method of claim 1 , wherein a transaction of the plurality of transactions represents a line item in a financial reporting instance document. | 6. The method of claim 1 , wherein a transaction of the plurality of transactions represents a line item in a financial reporting instance document. 7. The method of claim 6 , wherein the financial reporting instance document comprises an Extensible Business Reporting Language (XBRL) instance document. | 0.962963 |
7,873,616 | 20 | 26 | 20. A computer readable medium having stored thereon a set of instructions that when executed causes a computing device to perform a method comprising: define an a-priori score for a first node of an ontology; define an a-priori score for a second node of the ontology; determine a lowest common ancestor node in the ontology connecting the first node and the second node; defining an a-priori score for the lowest common ancestor node; calculate an inference from the first node to the second node using the a-priori score for the first node, the a-priori score for the second node, and the a-priori score for the lowest common ancestor node; calculate a personalized score for the second node by using the known personal score for the first node and a relationship of the second node and the first node in the ontology; identify, a qualifying concept from concepts in the ontology for which personalized scores have been computed, wherein, the qualifying concept that is identified from the concepts, is one that is associated a qualifying score among the personalized scores that have been computed for the concepts at the nodes of the ontology. | 20. A computer readable medium having stored thereon a set of instructions that when executed causes a computing device to perform a method comprising: define an a-priori score for a first node of an ontology; define an a-priori score for a second node of the ontology; determine a lowest common ancestor node in the ontology connecting the first node and the second node; defining an a-priori score for the lowest common ancestor node; calculate an inference from the first node to the second node using the a-priori score for the first node, the a-priori score for the second node, and the a-priori score for the lowest common ancestor node; calculate a personalized score for the second node by using the known personal score for the first node and a relationship of the second node and the first node in the ontology; identify, a qualifying concept from concepts in the ontology for which personalized scores have been computed, wherein, the qualifying concept that is identified from the concepts, is one that is associated a qualifying score among the personalized scores that have been computed for the concepts at the nodes of the ontology. 26. The method of claim 20 further comprising, calculating a personalized score for a user using a concept that is known to be liked by the user. | 0.858674 |
4,697,209 | 31 | 32 | 31. The method recited in claim 28 wherein the signal to be identified includes a video signal, and wherein the step of extracting the feature string includes the steps of detecting predetermined events in the video signal and determining the time intervals between detected predetermined events to generate the feature string. | 31. The method recited in claim 28 wherein the signal to be identified includes a video signal, and wherein the step of extracting the feature string includes the steps of detecting predetermined events in the video signal and determining the time intervals between detected predetermined events to generate the feature string. 32. The method recited in claim 31 wherein the step of detecting predetermined events includes the step of monitoring the light emanating from a display on which the video signal is displayed, and indicating a detected predetermined event when the amount of light emanating from the display changes by a predetermined amount. | 0.833162 |
9,715,542 | 1 | 15 | 1. A computerized method of determining relevancies of multiple objects to a search query, comprising: associating one or more of the multiple objects with user-entered tags as a result of user input, thereby defining one or more corresponding tag-object pairs, wherein each tag comprises one or more tag terms, each tag term comprising text, and wherein each association of an object with a tag comprises a tag object pair; associating an object with each tag term from the one or more tag terms, thereby defining one or more corresponding tag term object pairs, wherein at least one of the one or more tags comprises a string of multiple terms entered by a user; determining for each tag term object pair a tag term score indicating a degree of relevance between the tag term and the object, wherein a tag term score for an object X and a term A is a function of a combination comprising a total number of different terms in a tag database storing the tags, a total number of tags present in the tag database, a frequency with which the term A is present in the tag database, a number of different terms with which the object X has been tagged, a total number of tags associated with the object X, and a number of different objects that have been tagged with the term A; determining for one or more objects a term relevance score comprising combining the tag term scores from the tag term object pairs for each tag associated with each object; and determining a relevance score for each of the multiple objects for the search query, wherein the relevance score is influenced by tags associated with objects as a result of user input. | 1. A computerized method of determining relevancies of multiple objects to a search query, comprising: associating one or more of the multiple objects with user-entered tags as a result of user input, thereby defining one or more corresponding tag-object pairs, wherein each tag comprises one or more tag terms, each tag term comprising text, and wherein each association of an object with a tag comprises a tag object pair; associating an object with each tag term from the one or more tag terms, thereby defining one or more corresponding tag term object pairs, wherein at least one of the one or more tags comprises a string of multiple terms entered by a user; determining for each tag term object pair a tag term score indicating a degree of relevance between the tag term and the object, wherein a tag term score for an object X and a term A is a function of a combination comprising a total number of different terms in a tag database storing the tags, a total number of tags present in the tag database, a frequency with which the term A is present in the tag database, a number of different terms with which the object X has been tagged, a total number of tags associated with the object X, and a number of different objects that have been tagged with the term A; determining for one or more objects a term relevance score comprising combining the tag term scores from the tag term object pairs for each tag associated with each object; and determining a relevance score for each of the multiple objects for the search query, wherein the relevance score is influenced by tags associated with objects as a result of user input. 15. The method of claim 1 , wherein associating one or more of the multiple objects with tags comprises analyzing input given by a user conducting a search. | 0.896 |
8,265,923 | 9 | 10 | 9. The apparatus as set forth in claim 8 , wherein the model parameters optimization engine is configured to iteratively optimize values of the parameters of the conditional translation probability, the model parameters optimization engine in each iteration adding candidate aligned translations to the translation pool by sampling available candidate aligned translations in accordance with the conditional translation probability with parameter values of the current iteration. | 9. The apparatus as set forth in claim 8 , wherein the model parameters optimization engine is configured to iteratively optimize values of the parameters of the conditional translation probability, the model parameters optimization engine in each iteration adding candidate aligned translations to the translation pool by sampling available candidate aligned translations in accordance with the conditional translation probability with parameter values of the current iteration. 10. The method as set forth in claim 9 , wherein the iterative optimization process employs the bilingual evaluation understudy (BLEU) method. | 0.960946 |
9,047,414 | 18 | 19 | 18. The system of claim 17 , wherein the processing device is further to: receive an automated test script template; and generate the automated test script by writing the automated testing script command to the automated test script template. | 18. The system of claim 17 , wherein the processing device is further to: receive an automated test script template; and generate the automated test script by writing the automated testing script command to the automated test script template. 19. The system of claim 18 , wherein the test script template is an empty script program and the processing device is further to populate the empty script program with the automated testing script command to create an automated testing program executable by the testing framework system. | 0.917339 |
9,864,995 | 1 | 7 | 1. A method for customer contact handling at a customer service system, comprising: receiving, at a system server, contact text and contact metadata from a user communication device; determining, at the system server, semantic characteristics of the contact text based on semantic analysis of the contact text; identifying, at the system server, a user profile based on the contact metadata; retrieving, at the system server, user data associated with the identified user profile; determining, at the system server, a contact need classification based on the semantic characteristics and user data; selecting, at the system server, a service agent profile from a plurality of service agent profiles based on one or more of the contact need classification, semantic characteristics, and user data; initiating, by the system server, a contact event with an agent communication device associated with the selected service agent profile; and providing, by the system server, contact event data to the agent communication device. | 1. A method for customer contact handling at a customer service system, comprising: receiving, at a system server, contact text and contact metadata from a user communication device; determining, at the system server, semantic characteristics of the contact text based on semantic analysis of the contact text; identifying, at the system server, a user profile based on the contact metadata; retrieving, at the system server, user data associated with the identified user profile; determining, at the system server, a contact need classification based on the semantic characteristics and user data; selecting, at the system server, a service agent profile from a plurality of service agent profiles based on one or more of the contact need classification, semantic characteristics, and user data; initiating, by the system server, a contact event with an agent communication device associated with the selected service agent profile; and providing, by the system server, contact event data to the agent communication device. 7. The method of claim 1 , further comprising: receiving contact event text correspondence data; and determining semantic characteristics of the contact event text correspondence data based on semantic analysis of the contact event text correspondence data. | 0.539427 |
9,425,971 | 16 | 18 | 16. A computer program product comprising a non-transitory computer useable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: identify a set of users that share a common set of characteristics by determining an online status of each user in the set of users and determining that the set of users perform same or related activities within a bounded time period and a defined geographical area; dynamically create a shared communication space for the set of users; create shared space settings for a first user in the shared communication space, wherein the shared space settings define what communications to and from the shared communication space are permitted or prohibited for the first user, and control, on a per information item basis, what information items can be shared; send to the first user an invitation that invites the first user to join the shared communication space, the invitation including the shared space settings specifying on a per information item basis what can be shared by the first user; and in response to the first user joining the shared communication space based on the invitation: apply the shared space settings of the first user to the shared communication space; filter information items provided to the first user based on the shared space settings associated with the first user including identifying a set of receivers of an information item in the shared communication space, the set of receivers including the first user, and determining whether to send the information item to the first user based on determining whether a number of receivers in the set is larger than a particular size; output the filtered information items and instructions that cause display of a user interface including the filtered information items when the instructions are executed on a client device; and receive communications from other users of the set of users about the filtered information items in the shared communications space. | 16. A computer program product comprising a non-transitory computer useable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: identify a set of users that share a common set of characteristics by determining an online status of each user in the set of users and determining that the set of users perform same or related activities within a bounded time period and a defined geographical area; dynamically create a shared communication space for the set of users; create shared space settings for a first user in the shared communication space, wherein the shared space settings define what communications to and from the shared communication space are permitted or prohibited for the first user, and control, on a per information item basis, what information items can be shared; send to the first user an invitation that invites the first user to join the shared communication space, the invitation including the shared space settings specifying on a per information item basis what can be shared by the first user; and in response to the first user joining the shared communication space based on the invitation: apply the shared space settings of the first user to the shared communication space; filter information items provided to the first user based on the shared space settings associated with the first user including identifying a set of receivers of an information item in the shared communication space, the set of receivers including the first user, and determining whether to send the information item to the first user based on determining whether a number of receivers in the set is larger than a particular size; output the filtered information items and instructions that cause display of a user interface including the filtered information items when the instructions are executed on a client device; and receive communications from other users of the set of users about the filtered information items in the shared communications space. 18. The computer program product of claim 16 , wherein the set of users includes users of clients, and wherein the clients include at least one of a mobile phone and a gaming device. | 0.835443 |
9,986,093 | 1 | 3 | 1. A method of integrating to an external application for an agent in a web client application, the method comprising: starting an interaction with a client with the web client application by the agent; searching for relevant knowledge content through a third-party integration module using a graphical user interface, wherein the third-party integration module integrates with other systems and applications outside of a current system in order to search for the relevant knowledge content, wherein the other systems and applications outside of the current system are integrated into the graphical user interface; and completing the interaction with the client using the graphical user interface with enhanced input from the search step. | 1. A method of integrating to an external application for an agent in a web client application, the method comprising: starting an interaction with a client with the web client application by the agent; searching for relevant knowledge content through a third-party integration module using a graphical user interface, wherein the third-party integration module integrates with other systems and applications outside of a current system in order to search for the relevant knowledge content, wherein the other systems and applications outside of the current system are integrated into the graphical user interface; and completing the interaction with the client using the graphical user interface with enhanced input from the search step. 3. The method of claim 1 , wherein the interaction with the client is any one of a live telephone call, e-mail, face-to-face, or a web chat session with the client. | 0.613208 |
7,613,732 | 7 | 9 | 7. The method of claim 3 , wherein if the special character is a “−”, the hierarchy structure is traversed downward to the level indicated by the level indicator. | 7. The method of claim 3 , wherein if the special character is a “−”, the hierarchy structure is traversed downward to the level indicated by the level indicator. 9. The method of claim 7 , wherein if the hierarchy structure is an organization hierarchy structure and the level indicator indicates all levels, the hierarchy structure is traversed downward to obtain all subordinates in the hierarchy chain for the name in the entry. | 0.902818 |
9,015,086 | 1 | 5 | 1. A method comprising: generating semantic objects definitions and semantic relations definitions of a meta-model of business objects from a meta-model semantic network, the semantic relations definitions based on connections between semantic objects; forming a neural network based on usage of the semantic objects and the semantic relations, neural network configuration data, neural network training data, and calculated prediction data generated during usage of the neural network; forming a contextual network based on the neural network, the semantic objects definitions, the semantic relations definitions, the semantic objects definitions and the semantic relations definitions defining nodes that link a term to a knowledge domain and a concept; using at least one hardware processor of a machine to perform a statistical analysis of the connections between the semantic objects in the contextual network to identify stronger semantic relations; using the identified stronger semantic relations of the semantic objects in the contextual network to update the neural network; and updating the contextual network based on the updated neural network. | 1. A method comprising: generating semantic objects definitions and semantic relations definitions of a meta-model of business objects from a meta-model semantic network, the semantic relations definitions based on connections between semantic objects; forming a neural network based on usage of the semantic objects and the semantic relations, neural network configuration data, neural network training data, and calculated prediction data generated during usage of the neural network; forming a contextual network based on the neural network, the semantic objects definitions, the semantic relations definitions, the semantic objects definitions and the semantic relations definitions defining nodes that link a term to a knowledge domain and a concept; using at least one hardware processor of a machine to perform a statistical analysis of the connections between the semantic objects in the contextual network to identify stronger semantic relations; using the identified stronger semantic relations of the semantic objects in the contextual network to update the neural network; and updating the contextual network based on the updated neural network. 5. The method of claim 1 , further comprising: forming semantic relations regarding business functionality defined in existing business applications; and detecting the semantic relations in different business related documents. | 0.834064 |
6,067,517 | 15 | 20 | 15. A method for transcribing a segment of data that includes speech in one or more environments and non-speech data, comprising: inputting the data to a segmenter and producing a series of segments, each segment being given a type identifier tag selected from a predetermined set of classes, wherein it is assumed that the input data is produced by a parallel combination of models, each model corresponding to one of the predetermined classes, the identifier tag assigned to a segment being the class identifier tag of the model that gives the segment the highest probability, subject to certain constraints, wherein a number of classes that the acoustic input can be classified into are identified that represent the most acoustically dissimilar classes possible and, wherein the process of creating the models comprises identifying a feature space for the individual predetermined classes; and transcribing each type identifier tagged segment using a specific system created for that type. | 15. A method for transcribing a segment of data that includes speech in one or more environments and non-speech data, comprising: inputting the data to a segmenter and producing a series of segments, each segment being given a type identifier tag selected from a predetermined set of classes, wherein it is assumed that the input data is produced by a parallel combination of models, each model corresponding to one of the predetermined classes, the identifier tag assigned to a segment being the class identifier tag of the model that gives the segment the highest probability, subject to certain constraints, wherein a number of classes that the acoustic input can be classified into are identified that represent the most acoustically dissimilar classes possible and, wherein the process of creating the models comprises identifying a feature space for the individual predetermined classes; and transcribing each type identifier tagged segment using a specific system created for that type. 20. The method of claim 15, wherein the feature space for the model for non-speech is created by: taking a window of input speech every 10 milliseconds and computing the pitch; wherein the feature is the mean and the variance of the pitch across a plurality of consecutive windows. | 0.697849 |
8,566,293 | 3 | 5 | 3. The method of claim 2 , wherein the information model is used as both an analysis and runtime template. | 3. The method of claim 2 , wherein the information model is used as both an analysis and runtime template. 5. The method of claim 3 , wherein for runtime management, the information model is instantiated into a set of data models whose objects, attributes, and relationships are then “filled in” with measured data. | 0.912971 |
9,241,223 | 1 | 22 | 1. A method of directionally filtering portions of an audible signal, the method comprising: determining one or more directional indicator values from composite audible signal data, the composite audible signal data including a respective audible signal data component from each of a plurality of audio sensors; determining a gain function from the one or more directional indicator values, the gain function targeting one or more portions of the composite audible signal data, wherein generating the gain function from the one or more directional indicator values includes determining, for each directional indicator value, a respective component-gain function based on the directional indicator value and a corresponding target value associated with the directional indicator value, and the respective component-gain function includes a distance function of the directional indicator value and the corresponding target value; and filtering the composite audible signal data using the gain function in order to produce directionally filtered audible signal data, the directionally filtered audible signal data including one or more portions of the composite audible signal data that have been changed by filtering with the gain function. | 1. A method of directionally filtering portions of an audible signal, the method comprising: determining one or more directional indicator values from composite audible signal data, the composite audible signal data including a respective audible signal data component from each of a plurality of audio sensors; determining a gain function from the one or more directional indicator values, the gain function targeting one or more portions of the composite audible signal data, wherein generating the gain function from the one or more directional indicator values includes determining, for each directional indicator value, a respective component-gain function based on the directional indicator value and a corresponding target value associated with the directional indicator value, and the respective component-gain function includes a distance function of the directional indicator value and the corresponding target value; and filtering the composite audible signal data using the gain function in order to produce directionally filtered audible signal data, the directionally filtered audible signal data including one or more portions of the composite audible signal data that have been changed by filtering with the gain function. 22. The method of claim 1 , wherein the respective component-gain function includes a sigmoid function of the distance function. | 0.898574 |
9,686,150 | 2 | 3 | 2. The monitoring system of claim 1 , wherein the descriptions of the plurality of computing components in the registry comprise relationship information indicating a dependency between two computing components of the plurality of computing components. | 2. The monitoring system of claim 1 , wherein the descriptions of the plurality of computing components in the registry comprise relationship information indicating a dependency between two computing components of the plurality of computing components. 3. The monitoring system of claim 2 , wherein the at least one performance requirement for the first SLA specifies performance for a single call of the associated computing component and wherein the first event indicates violation of the single call. | 0.95283 |
8,238,666 | 2 | 3 | 2. The method according to claim 1 , wherein said at least one of the plurality of template shapes is a set of candidate template shapes selected from a set of template shapes. | 2. The method according to claim 1 , wherein said at least one of the plurality of template shapes is a set of candidate template shapes selected from a set of template shapes. 3. The method according to claim 2 , wherein the candidate template shapes are selected using a machine learning classifier. | 0.939571 |
10,134,388 | 5 | 9 | 5. A computer-implemented method comprising: determining a speech recognition model, wherein the speech recognition model was trained by: determining first characteristics corresponding to a first word, determining second characteristics corresponding to a second word, determining that the first characteristics are similar to the second characteristics, identifying, in a lexicon, a variation of the second word, wherein the variation of the second word differs from the second word by at least one letter, creating, based at least in part on determining that the first characteristics are similar to the second characteristics and based at least in part on identifying the variation of the second word, a variation of the first word, wherein the variation of the first word differs from the first word by the at least one letter, and training the speech recognition model to recognize the first word and the variation of the first word; and performing speech recognition using the speech recognition model to determine speech recognition output including the variation of the first word. | 5. A computer-implemented method comprising: determining a speech recognition model, wherein the speech recognition model was trained by: determining first characteristics corresponding to a first word, determining second characteristics corresponding to a second word, determining that the first characteristics are similar to the second characteristics, identifying, in a lexicon, a variation of the second word, wherein the variation of the second word differs from the second word by at least one letter, creating, based at least in part on determining that the first characteristics are similar to the second characteristics and based at least in part on identifying the variation of the second word, a variation of the first word, wherein the variation of the first word differs from the first word by the at least one letter, and training the speech recognition model to recognize the first word and the variation of the first word; and performing speech recognition using the speech recognition model to determine speech recognition output including the variation of the first word. 9. The computer-implemented method of claim 5 , wherein the speech recognition model was further trained by determining a training corpus comprising usage examples of a plurality of words, the plurality including the first word, the second word and the variation of the second word, and wherein: determining the first characteristics comprises determining a first vector representing usage of the first word in the training corpus, determining the second characteristics comprises determining a second vector representing usage of the second word in the training corpus, and determining that the first characteristics are similar to the second characteristics comprises determining that the first vector is within a threshold distance of the second vector. | 0.642384 |
8,296,747 | 6 | 8 | 6. The system according to claim 5 , wherein the determination section determines, for each character string output instruction for outputting a character string constant, whether or not to previously convert the character code set of the character string constant, on the basis of a number of characters of a character string to be outputted. | 6. The system according to claim 5 , wherein the determination section determines, for each character string output instruction for outputting a character string constant, whether or not to previously convert the character code set of the character string constant, on the basis of a number of characters of a character string to be outputted. 8. The system according to claim 6 , wherein the determination section determines not to previously convert the character code set of a character string to be outputted before executing the output program, on condition that at least one of character string output instructions to be successively executed, whose total number of characters of a character string constant to be outputted is less than a predetermined reference value, is successively executed after another character string output instruction for outputting the value of a character string variable, and is successively executed before still another character string output instruction for outputting the value of a character string variable. | 0.803013 |
9,819,759 | 16 | 23 | 16. A computer system comprising: a processor; a memory comprising computer code executed using the processor, in which the computer code implements: a computing platform to: identify a first social site, the first social site having a first access interface comprising a first application programming interface (API) specific to the first social sites identifying a social event corresponding to a post on the first social site or a message on the first social site at the first social site, the social event corresponding to a first event type; sharing the social event from the first social site to a second social site by implementing an integration platform located separate from social sites, the sharing comprising the steps of: (1) receiving the social event from the first social site; (2) Identifying the second social site associated with a user that created the social event at the first social site, the second social site identified on a basis of having a supported event type that corresponds to the first event type associated with the social event, the second social site having a second access interface, that comprises a second API specific to the second social site and different from the first access interface; and (3) modifying the social event into a modified social event of the supported event type for the second social site; and sending the modified social event of the supported event type to the second social site through the second access interface having the second API specific to the second social site; creating the social event on the first social site by interacting with an application, wherein creation of the social event results in sending the social event to the first social site over a request path, the first social site responding to the social event with an acknowledgement that the first social site processed the social event; perform security processing on the social event; classifying the social event into at least one classification; performing mapping to standardize a set of common social networking concepts, wherein a mapping function comprises: receiving the social event from the first social site; determining semantics in the social event from the first social site, and mapping the social event from the first social site to a second social event on a second social event; contacting a network interface to broadcast the modified social event to additional sites, wherein the integration platform is configured by configuration data, wherein the configuration data comprises user preferences, wherein the modifying the social event into a modified social event further comprises at least one of modifying a header, modifying a destination address, modifying a source address, modifying a format, or modifying a message content. | 16. A computer system comprising: a processor; a memory comprising computer code executed using the processor, in which the computer code implements: a computing platform to: identify a first social site, the first social site having a first access interface comprising a first application programming interface (API) specific to the first social sites identifying a social event corresponding to a post on the first social site or a message on the first social site at the first social site, the social event corresponding to a first event type; sharing the social event from the first social site to a second social site by implementing an integration platform located separate from social sites, the sharing comprising the steps of: (1) receiving the social event from the first social site; (2) Identifying the second social site associated with a user that created the social event at the first social site, the second social site identified on a basis of having a supported event type that corresponds to the first event type associated with the social event, the second social site having a second access interface, that comprises a second API specific to the second social site and different from the first access interface; and (3) modifying the social event into a modified social event of the supported event type for the second social site; and sending the modified social event of the supported event type to the second social site through the second access interface having the second API specific to the second social site; creating the social event on the first social site by interacting with an application, wherein creation of the social event results in sending the social event to the first social site over a request path, the first social site responding to the social event with an acknowledgement that the first social site processed the social event; perform security processing on the social event; classifying the social event into at least one classification; performing mapping to standardize a set of common social networking concepts, wherein a mapping function comprises: receiving the social event from the first social site; determining semantics in the social event from the first social site, and mapping the social event from the first social site to a second social event on a second social event; contacting a network interface to broadcast the modified social event to additional sites, wherein the integration platform is configured by configuration data, wherein the configuration data comprises user preferences, wherein the modifying the social event into a modified social event further comprises at least one of modifying a header, modifying a destination address, modifying a source address, modifying a format, or modifying a message content. 23. The computer system of claim 16 , wherein the social event comprises at least one of, a wall post, a status update, a news feed, a like, and a friend recommendation. | 0.700355 |
7,634,766 | 8 | 10 | 8. A system for analyzing a target system, comprising: a processor; a memory; a meta model comprising information about attributes, characteristics, and relationships of a characteristics model, wherein the characteristics model comprises a plurality of artifacts, at least one relationship between a first one of the plurality of artifacts and a second one of the plurality of artifacts, and at least one characteristic associated with each of the plurality of artifacts, wherein the characteristics model is stored on the memory; the target system comprising a plurality of characteristics, wherein the target system comprises a combination of hardware and software; at least one characteristics extractor configured to obtain at least one of the plurality of characteristics from the target system, wherein the at least one of the plurality of characteristics is defined in the characteristics model; a characteristics store configured to store the at least one of the plurality of characteristics obtained from the target system; and a query engine, executing on the processor, configured to: verify at least one query by traversing the meta model to determine whether each component within the at least one query is defined in the meta model; and analyze, in response to the verifying, the target system by issuing the at least one query to the characteristics store; and obtain an analysis result in response to the at least one query generating the characteristics extractor associated with the characteristics model; and generating a characteristics store application programming interface (API) associated with the characteristics model, wherein the characteristics extractor uses the characteristics store API to store each of the plurality of characteristics in the characteristics store. | 8. A system for analyzing a target system, comprising: a processor; a memory; a meta model comprising information about attributes, characteristics, and relationships of a characteristics model, wherein the characteristics model comprises a plurality of artifacts, at least one relationship between a first one of the plurality of artifacts and a second one of the plurality of artifacts, and at least one characteristic associated with each of the plurality of artifacts, wherein the characteristics model is stored on the memory; the target system comprising a plurality of characteristics, wherein the target system comprises a combination of hardware and software; at least one characteristics extractor configured to obtain at least one of the plurality of characteristics from the target system, wherein the at least one of the plurality of characteristics is defined in the characteristics model; a characteristics store configured to store the at least one of the plurality of characteristics obtained from the target system; and a query engine, executing on the processor, configured to: verify at least one query by traversing the meta model to determine whether each component within the at least one query is defined in the meta model; and analyze, in response to the verifying, the target system by issuing the at least one query to the characteristics store; and obtain an analysis result in response to the at least one query generating the characteristics extractor associated with the characteristics model; and generating a characteristics store application programming interface (API) associated with the characteristics model, wherein the characteristics extractor uses the characteristics store API to store each of the plurality of characteristics in the characteristics store. 10. The system of claim 8 , wherein extracting the contents of the characteristics model comprises obtaining information about the characteristics model to create a meta model instance of the characteristics model using a meta model schema associated with the meta model. | 0.781804 |
7,516,050 | 1 | 12 | 1. A method executed in a computer system for estimating a probability associated with a parent variable that an event corresponding to the parent variable will occur, the method comprises: retrieving data as data strings from a data source; producing a dataset from the retrieved data strings; building a statistical model of parent-child relationships from data strings in the dataset by: determining incidence values for the data strings in the dataset; and concatenating the incident values with the data strings to provide child variables; analyzing the child variables and the parent variable to produce statistical relationships between the child variables and the parent variable; determining probabilities values for the event based on the determined parent child relationships; and building an ontological representation of the data based on subsequent conditional probabilities values. | 1. A method executed in a computer system for estimating a probability associated with a parent variable that an event corresponding to the parent variable will occur, the method comprises: retrieving data as data strings from a data source; producing a dataset from the retrieved data strings; building a statistical model of parent-child relationships from data strings in the dataset by: determining incidence values for the data strings in the dataset; and concatenating the incident values with the data strings to provide child variables; analyzing the child variables and the parent variable to produce statistical relationships between the child variables and the parent variable; determining probabilities values for the event based on the determined parent child relationships; and building an ontological representation of the data based on subsequent conditional probabilities values. 12. The method of claim 1 wherein the text strings represent any alphanumeric text data. | 0.866667 |
9,613,125 | 1 | 15 | 1. A method comprising: storing in a database a first annotation and a second annotation, the first annotation relating to a first content unit and comprising a first semantic label and first content, the first semantic label comprising a term that does not appear in the first content and indicating a semantic classification of the first content, the second annotation relating to a second content unit and comprising a second semantic label and second content, the second semantic label comprising a term that does not appear in the second content and indicating a semantic classification of the second content, the semantic classification of the second content being different from the semantic classification of the first content, wherein the semantic classification of the first content indicates a meaning of the first content in context of the first content unit, wherein the first content does not explicitly appear in the first content unit, the term that indicates the semantic classification of the first content indicating a meaning of the first content in context of the first content unit from which the first content was determined, wherein the second content is a text excerpt of text of the second content unit, wherein the semantic classification of the second content indicates that the second content is an organizational and/or grammatical element of the text of the second content unit, wherein the storing comprises storing the first semantic label for the first annotation and the second semantic label for the second annotation in a first table of the database, and storing the first content of the first annotation and the second content of the second annotation in at least one second table of the database different from the first table. | 1. A method comprising: storing in a database a first annotation and a second annotation, the first annotation relating to a first content unit and comprising a first semantic label and first content, the first semantic label comprising a term that does not appear in the first content and indicating a semantic classification of the first content, the second annotation relating to a second content unit and comprising a second semantic label and second content, the second semantic label comprising a term that does not appear in the second content and indicating a semantic classification of the second content, the semantic classification of the second content being different from the semantic classification of the first content, wherein the semantic classification of the first content indicates a meaning of the first content in context of the first content unit, wherein the first content does not explicitly appear in the first content unit, the term that indicates the semantic classification of the first content indicating a meaning of the first content in context of the first content unit from which the first content was determined, wherein the second content is a text excerpt of text of the second content unit, wherein the semantic classification of the second content indicates that the second content is an organizational and/or grammatical element of the text of the second content unit, wherein the storing comprises storing the first semantic label for the first annotation and the second semantic label for the second annotation in a first table of the database, and storing the first content of the first annotation and the second content of the second annotation in at least one second table of the database different from the first table. 15. The method of claim 1 , wherein the semantic classification of the first content indicates a meaning of the first content in context of a portion of the first content unit from which the first content was determined. | 0.961131 |
7,895,240 | 1 | 2 | 1. A method for managing information comprising: generating a first database in a first memory device; storing, by an administrator via a server system, a plurality of predefined questions in the first database, wherein the plurality of predefined questions relate to project information and include at least a first predefined question and a second predefined question; storing, by the administrator, a plurality of predefined answer options related to the project information, wherein each predefined answer option corresponds to one of the plurality of predefined questions; associating, by the administrator, each of the plurality of predefined answer options with a task by pre-defining, within the first database, a task to be performed based on each of the plurality of predefined answer options; associating, by the administrator, a plurality of tools used to complete a task with each task, wherein said plurality of tools includes at least one expert on a task; providing, via a computer, to a user, the plurality of predefined questions and the plurality of predefined answer options; receiving a plurality of answers from the user, wherein the plurality of answers are chosen by the user from the provided plurality of predefined answer options, and wherein at least one answer option associated with the second predefined question is modified based on an answer from the first predefined question from the user, wherein modifying at least one answer option comprises at least one of adding at least one answer option associated with the second predefined question and removing at least one answer option associated with the second predefined question; determining, by the computer, a task and tools based on the plurality of answers provided by the user; creating at least one additional database in a second memory device based on the plurality of predefined answer options; associating the first database with the at least one additional database based on the plurality of answers provided by the user without making a change to at least one source code; populating the at least one additional database with the determined task; and prompting the user to customize the determined task within the at least one additional database, without changing the at least one source code, after the at least one additional database has been populated. | 1. A method for managing information comprising: generating a first database in a first memory device; storing, by an administrator via a server system, a plurality of predefined questions in the first database, wherein the plurality of predefined questions relate to project information and include at least a first predefined question and a second predefined question; storing, by the administrator, a plurality of predefined answer options related to the project information, wherein each predefined answer option corresponds to one of the plurality of predefined questions; associating, by the administrator, each of the plurality of predefined answer options with a task by pre-defining, within the first database, a task to be performed based on each of the plurality of predefined answer options; associating, by the administrator, a plurality of tools used to complete a task with each task, wherein said plurality of tools includes at least one expert on a task; providing, via a computer, to a user, the plurality of predefined questions and the plurality of predefined answer options; receiving a plurality of answers from the user, wherein the plurality of answers are chosen by the user from the provided plurality of predefined answer options, and wherein at least one answer option associated with the second predefined question is modified based on an answer from the first predefined question from the user, wherein modifying at least one answer option comprises at least one of adding at least one answer option associated with the second predefined question and removing at least one answer option associated with the second predefined question; determining, by the computer, a task and tools based on the plurality of answers provided by the user; creating at least one additional database in a second memory device based on the plurality of predefined answer options; associating the first database with the at least one additional database based on the plurality of answers provided by the user without making a change to at least one source code; populating the at least one additional database with the determined task; and prompting the user to customize the determined task within the at least one additional database, without changing the at least one source code, after the at least one additional database has been populated. 2. The method in accordance with claim 1 wherein at least one of said generating and said creating is performed without making a change to at least one source code. | 0.870662 |
10,120,929 | 6 | 10 | 6. A system for categorizing items, the system comprising: a data store adapted to store a plurality of hierarchically organized categories for items, each of the hierarchically organized categories including at least one category attribute and corresponding category attribute value; and an item categorization service in communication with the data store, the item categorization service adapted to: receive item information associated with an item of interest, the item information comprising at least one item attribute and corresponding item attribute value for the item of interest; assign a first category for the item of interest from the hierarchically organized categories stored by the data store using the item information; determine one or more rules associated with the assigned first category; identify one or more second category candidates using the one or more rules and a relevance value associated with the item information and the at least one second category candidate; determine which of the second category candidates has the most second category candidate attributes of the second category candidates; and select the second category candidate that has the most second category candidate attributes as the second category of the item of interest. | 6. A system for categorizing items, the system comprising: a data store adapted to store a plurality of hierarchically organized categories for items, each of the hierarchically organized categories including at least one category attribute and corresponding category attribute value; and an item categorization service in communication with the data store, the item categorization service adapted to: receive item information associated with an item of interest, the item information comprising at least one item attribute and corresponding item attribute value for the item of interest; assign a first category for the item of interest from the hierarchically organized categories stored by the data store using the item information; determine one or more rules associated with the assigned first category; identify one or more second category candidates using the one or more rules and a relevance value associated with the item information and the at least one second category candidate; determine which of the second category candidates has the most second category candidate attributes of the second category candidates; and select the second category candidate that has the most second category candidate attributes as the second category of the item of interest. 10. The system of claim 6 , wherein the item classification service is further adapted to identify a category attribute of the assigned first category and select the first category from a plurality of first category candidates, and wherein at least one of the first categories is not associated with the identified category attribute of the assigned first category. | 0.691723 |
8,422,656 | 1 | 16 | 1. A method for implementing customized rules for controlling customer communications, comprising: processing a request received from a remote source to customize a rule for controlling customer communications; providing an entry menu for customizing rules for controlling customer communications based upon receipt of the request to customize a rule for controlling customer communications, the entry menu including a selectable option to modify an existing customized rule for controlling customer communications and a selectable option to create a new customized rule for controlling customer communications; processing a request received via the entry menu to create a new customized rule for controlling customer communications; providing, based upon receipt of the request to create a new customized rule for controlling customer communications, an initial selection criteria menu to create the new customized rule for controlling customer communications, the initial selection criteria menu indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; processing a response received via the initial selection criteria menu indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; determining from the response received via the initial selection criteria menu whether the new customized rule will be built using a preexisting template; when the new customized rule will be built using a preexisting template, providing a list of preexisting templates for creating new customized rules for controlling customer communications, processing a received selection of a preexisting template from the list of preexisting templates, providing the selected preexisting template, accepting input to populate the selected preexisting template, and storing a new customized rule based on the selected preexisting template and including accepted input; when the new customized rule will be built without using a preexisting template, providing initial blank rule criteria for creating a new customized rule for controlling customer communications, processing a received selection of initial criteria from the initial blank rule criteria, providing a list of rule conditions for the selected initial criteria for the new customized rule, processing a received selection of rule conditions for the selected initial criteria for the new customized rule, and creating and storing a new customized rule based on the selected initial criteria and the selected rule conditions; providing a display describing the new customized rule; and processing communications in accordance with the stored new customized rule, wherein the stored new customized rule is implemented at an internal network node of a communications service provider in accordance with requests and selections received from customers using customer equipment, and wherein the stored new customized rule further includes a selected disposition for when the selected initial criteria and selected rule conditions are met. | 1. A method for implementing customized rules for controlling customer communications, comprising: processing a request received from a remote source to customize a rule for controlling customer communications; providing an entry menu for customizing rules for controlling customer communications based upon receipt of the request to customize a rule for controlling customer communications, the entry menu including a selectable option to modify an existing customized rule for controlling customer communications and a selectable option to create a new customized rule for controlling customer communications; processing a request received via the entry menu to create a new customized rule for controlling customer communications; providing, based upon receipt of the request to create a new customized rule for controlling customer communications, an initial selection criteria menu to create the new customized rule for controlling customer communications, the initial selection criteria menu indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; processing a response received via the initial selection criteria menu indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; determining from the response received via the initial selection criteria menu whether the new customized rule will be built using a preexisting template; when the new customized rule will be built using a preexisting template, providing a list of preexisting templates for creating new customized rules for controlling customer communications, processing a received selection of a preexisting template from the list of preexisting templates, providing the selected preexisting template, accepting input to populate the selected preexisting template, and storing a new customized rule based on the selected preexisting template and including accepted input; when the new customized rule will be built without using a preexisting template, providing initial blank rule criteria for creating a new customized rule for controlling customer communications, processing a received selection of initial criteria from the initial blank rule criteria, providing a list of rule conditions for the selected initial criteria for the new customized rule, processing a received selection of rule conditions for the selected initial criteria for the new customized rule, and creating and storing a new customized rule based on the selected initial criteria and the selected rule conditions; providing a display describing the new customized rule; and processing communications in accordance with the stored new customized rule, wherein the stored new customized rule is implemented at an internal network node of a communications service provider in accordance with requests and selections received from customers using customer equipment, and wherein the stored new customized rule further includes a selected disposition for when the selected initial criteria and selected rule conditions are met. 16. The method according to claim 1 , further comprising: overriding the stored new customized rule when an originator of a communication enters an override indicator and processing the communication in accordance with the override indicator. | 0.726244 |
8,572,107 | 1 | 4 | 1. A horizontal anomaly detection method comprising: receiving a plurality of descriptions describing a plurality of objects, each object of the plurality of objects being described by a plurality of different information sources, wherein each individual information source of the plurality of information sources captures a plurality of similarity relationships between the plurality of objects; generating a similarity matrix from the plurality of different information sources, wherein entries of the similarity matrix represent quantitative scores of similarity between pairs of the plurality of objects; and identifying at least one horizontal anomaly within the plurality of objects from the similarity matrix, wherein the horizontal anomalies each comprise a clustering of at least two objects of the plurality of objects into a common cluster based on a first information source of the plurality of different information sources and simultaneously clustering the at least two objects of the plurality of objects into different clusters based on a second information source of the plurality of different information sources, wherein the steps of receiving the descriptions, generating the similarity matrix, and identifying the at least one horizontal anomalies are performed using a computer system, and wherein combining the information sources comprises; placing each individual similarity matrix along a block diagonal of the similarity matrix; and filling off-diagonal entries of the similarity matrix using weighted identity matrices, wherein a weight of the weighted identity matrices is a constraint on relationships across the plurality of information sources. | 1. A horizontal anomaly detection method comprising: receiving a plurality of descriptions describing a plurality of objects, each object of the plurality of objects being described by a plurality of different information sources, wherein each individual information source of the plurality of information sources captures a plurality of similarity relationships between the plurality of objects; generating a similarity matrix from the plurality of different information sources, wherein entries of the similarity matrix represent quantitative scores of similarity between pairs of the plurality of objects; and identifying at least one horizontal anomaly within the plurality of objects from the similarity matrix, wherein the horizontal anomalies each comprise a clustering of at least two objects of the plurality of objects into a common cluster based on a first information source of the plurality of different information sources and simultaneously clustering the at least two objects of the plurality of objects into different clusters based on a second information source of the plurality of different information sources, wherein the steps of receiving the descriptions, generating the similarity matrix, and identifying the at least one horizontal anomalies are performed using a computer system, and wherein combining the information sources comprises; placing each individual similarity matrix along a block diagonal of the similarity matrix; and filling off-diagonal entries of the similarity matrix using weighted identity matrices, wherein a weight of the weighted identity matrices is a constraint on relationships across the plurality of information sources. 4. The horizontal anomaly detection method of claim 1 , wherein higher quantitative scores correspond to anomalies. | 0.815113 |
7,827,028 | 36 | 37 | 36. An automated translation machine for translating a source language into a destination language, said translation machine comprising: means for receiving, at a translation module, at least one sentence in the source language; means for producing destination language translations of the at least one sentence, including destination language words corresponding to words of the source language sentence, independently of any need for a source language treebank; means for assigning syntactic labels indicating a syntactic category to the destination language words; means for searching among and statistically ranking, with a translingual parsing model, a plurality of candidate parses of the destination language words, each candidate parse having: elements labeled with destination language words corresponding to words of the source language sentence; syntactic labels indicating a syntactic category of the elements; and role labels indicating relationships between the elements; means for selecting the highest statistically ranked parse for the at least one sentence; and means for rearranging the parse using the syntactic and role labels, in accordance with word order conventions of the destination language to generate a translingual parse of the source language sentence. | 36. An automated translation machine for translating a source language into a destination language, said translation machine comprising: means for receiving, at a translation module, at least one sentence in the source language; means for producing destination language translations of the at least one sentence, including destination language words corresponding to words of the source language sentence, independently of any need for a source language treebank; means for assigning syntactic labels indicating a syntactic category to the destination language words; means for searching among and statistically ranking, with a translingual parsing model, a plurality of candidate parses of the destination language words, each candidate parse having: elements labeled with destination language words corresponding to words of the source language sentence; syntactic labels indicating a syntactic category of the elements; and role labels indicating relationships between the elements; means for selecting the highest statistically ranked parse for the at least one sentence; and means for rearranging the parse using the syntactic and role labels, in accordance with word order conventions of the destination language to generate a translingual parse of the source language sentence. 37. The automated translation machine of claim 36 , comprising means for generating the translingual parsing model. | 0.93709 |
9,537,674 | 10 | 11 | 10. A method as defined in claim 1 , including communicating with a message service that includes the inbox to gather the size information. | 10. A method as defined in claim 1 , including communicating with a message service that includes the inbox to gather the size information. 11. A method as defined in claim 10 , including sending a request to the message service to prompt the message service to generate the size information. | 0.953317 |
10,133,726 | 7 | 9 | 7. Apparatus comprising: at least one processor; and a computer-readable storage medium storing processor-executable instructions that, when executed by the at least one processor, perform a method comprising: performing an automatic fact extraction, wherein performing the automatic fact extraction comprises automatically extracting an initial set of one or more medical facts from a freeform text narrative provided by a health care provider; outputting, for presentation to a user reviewing a result of the automatic fact extraction, one or more extracted facts comprising at least some of the initial set of one or more medical facts; in response to receiving, from the user, an indication that at least one first fact of the one or more extracted facts should not have been extracted from the freeform text narrative and/or that at least one second fact that was not extracted from the freeform text narrative should have been extracted from the freeform text narrative, performing the automatic fact extraction again on at least part of the freeform text narrative using the indication that the at least one first fact should not have been extracted and/or that the at least one second fact that was not extracted should have been extracted to extract a second set of one or more medical facts from the freeform text narrative that is different from the initial set of one or more medical facts; and in response to receiving, from the user, a second indication that the at least one first fact of the one or more extracted facts was correctly extracted from the freeform text narrative, storing information indicating that the at least one first fact was extracted from the freeform text narrative. | 7. Apparatus comprising: at least one processor; and a computer-readable storage medium storing processor-executable instructions that, when executed by the at least one processor, perform a method comprising: performing an automatic fact extraction, wherein performing the automatic fact extraction comprises automatically extracting an initial set of one or more medical facts from a freeform text narrative provided by a health care provider; outputting, for presentation to a user reviewing a result of the automatic fact extraction, one or more extracted facts comprising at least some of the initial set of one or more medical facts; in response to receiving, from the user, an indication that at least one first fact of the one or more extracted facts should not have been extracted from the freeform text narrative and/or that at least one second fact that was not extracted from the freeform text narrative should have been extracted from the freeform text narrative, performing the automatic fact extraction again on at least part of the freeform text narrative using the indication that the at least one first fact should not have been extracted and/or that the at least one second fact that was not extracted should have been extracted to extract a second set of one or more medical facts from the freeform text narrative that is different from the initial set of one or more medical facts; and in response to receiving, from the user, a second indication that the at least one first fact of the one or more extracted facts was correctly extracted from the freeform text narrative, storing information indicating that the at least one first fact was extracted from the freeform text narrative. 9. The apparatus of claim 7 , wherein receiving the user's indication comprises receiving a change to a list of facts, wherein the change to the list of facts comprises adding to and/or removing from the list at least one fact included in the one or more extracted facts. | 0.808345 |
8,572,062 | 6 | 10 | 6. A system, comprising: a computer processor; and storage coupled to the computer processor, wherein the storage stores a program, and wherein the computer processor executes the program to perform operations, wherein the operations comprise: obtaining a document with multiple subsets of pages that includes a different internal index set associated with each subset of pages from among the multiple subsets of pages, wherein each different internal index is located within a first area on a page within the associated subset of pages, is relevant to the page and subsequent pages in the associated subset of pages until one of another internal index set within the document is found and an end of the document is reached, and includes one or more name-value pairs, and wherein the first area is ignored by an application that processes a second area of the document; extracting the one or more name-value pairs from each different internal index set, wherein each of the one or more name-value pairs provides specific information about the document for use in identifying the document; and storing the extracted one or more-name value pairs in a table in a database to enable subsequent searching for the document, wherein, for a name-value pair, the name corresponds to a column name in the table, and the value corresponds to a value stored in a row for a column having the name. | 6. A system, comprising: a computer processor; and storage coupled to the computer processor, wherein the storage stores a program, and wherein the computer processor executes the program to perform operations, wherein the operations comprise: obtaining a document with multiple subsets of pages that includes a different internal index set associated with each subset of pages from among the multiple subsets of pages, wherein each different internal index is located within a first area on a page within the associated subset of pages, is relevant to the page and subsequent pages in the associated subset of pages until one of another internal index set within the document is found and an end of the document is reached, and includes one or more name-value pairs, and wherein the first area is ignored by an application that processes a second area of the document; extracting the one or more name-value pairs from each different internal index set, wherein each of the one or more name-value pairs provides specific information about the document for use in identifying the document; and storing the extracted one or more-name value pairs in a table in a database to enable subsequent searching for the document, wherein, for a name-value pair, the name corresponds to a column name in the table, and the value corresponds to a value stored in a row for a column having the name. 10. The system of claim 6 , wherein the operations further comprise: in response to receiving a search request, identifying the document based on the search request matching at least one name-value pair stored in the database, wherein the at least one name-value pair is in an internal index set in the document. | 0.686117 |
8,386,437 | 1 | 7 | 1. A method for document management comprising: automatically acquiring image logs for all input documents being processed by image output devices within an organization, each image log comprising image data and an associated record for an input document being processed by one of at least one image output device within the organization, whereby image data is automatically acquired for all documents being processed by the organization's image output devices, without provision for a user to select whether a document image should be logged; automatically sending all of the image logs from the image output devices to an image log management system and storing the image logs in memory until a search for similar documents is performed; for each of the acquired and stored image logs, performing the search for similar documents and automatically retrieving similar documents, including identifying keywords extracted from the acquired image data, and based on the keywords, performing a search among previously acquired documents archived in a computer readable storage medium and accessible electronic documents stored in at least one other document repository to retrieve similar documents; and where a similar document is retrieved, computing a measure of similarity between the retrieved similar document and the input document; and based on the computed similarity, determining whether the retrieved document is a matching document and, if so, storing a location of the retrieved matching document whereby for the input document, a location of each retrieved matching document is stored; and providing a procedure for ensuring that a single version of the input document is archived in the computer-readable storage medium, the version being selected from the captured image data and any identified matching documents, except optionally where the job log indicates that at least one of the retrieved matching document locations is a public document source; the method further comprising: where the retrieved document has access controls, including a reference to the access controls of the retrieved document in the stored job log and further including at least one of: a) storing user information from the record of the image log in the stored job log, whereby a leak of an access controlled document is attributable to the user which caused the input document to be processed by the image output device; and b) blocking processing of the input document by the image output device where the access controls of the retrieved matching document indicate that such processing should be blocked. | 1. A method for document management comprising: automatically acquiring image logs for all input documents being processed by image output devices within an organization, each image log comprising image data and an associated record for an input document being processed by one of at least one image output device within the organization, whereby image data is automatically acquired for all documents being processed by the organization's image output devices, without provision for a user to select whether a document image should be logged; automatically sending all of the image logs from the image output devices to an image log management system and storing the image logs in memory until a search for similar documents is performed; for each of the acquired and stored image logs, performing the search for similar documents and automatically retrieving similar documents, including identifying keywords extracted from the acquired image data, and based on the keywords, performing a search among previously acquired documents archived in a computer readable storage medium and accessible electronic documents stored in at least one other document repository to retrieve similar documents; and where a similar document is retrieved, computing a measure of similarity between the retrieved similar document and the input document; and based on the computed similarity, determining whether the retrieved document is a matching document and, if so, storing a location of the retrieved matching document whereby for the input document, a location of each retrieved matching document is stored; and providing a procedure for ensuring that a single version of the input document is archived in the computer-readable storage medium, the version being selected from the captured image data and any identified matching documents, except optionally where the job log indicates that at least one of the retrieved matching document locations is a public document source; the method further comprising: where the retrieved document has access controls, including a reference to the access controls of the retrieved document in the stored job log and further including at least one of: a) storing user information from the record of the image log in the stored job log, whereby a leak of an access controlled document is attributable to the user which caused the input document to be processed by the image output device; and b) blocking processing of the input document by the image output device where the access controls of the retrieved matching document indicate that such processing should be blocked. 7. The method of claim 1 , wherein the similarity computation classifies retrieved documents having a threshold computed similarity as being a match, a revision, or a related document. | 0.923205 |
8,788,521 | 2 | 6 | 2. The information processing device according to claim 1 , wherein the relevant word generating unit has: a relevant word candidate generating unit that generates candidates of the relevant words from the first word; and a relevant word determining unit that determines the relevant word from the candidates. | 2. The information processing device according to claim 1 , wherein the relevant word generating unit has: a relevant word candidate generating unit that generates candidates of the relevant words from the first word; and a relevant word determining unit that determines the relevant word from the candidates. 6. The information processing device according to claim 2 , comprising: a second word acquiring unit that acquires a second word different from the first word, wherein the relevant word candidate generating unit generates the candidates containing a combination of a character string of the first word and a character string of the second word. | 0.863057 |
9,536,528 | 11 | 13 | 11. The method of claim 1 , wherein evaluating the speech data, or a transcription of the candidate hotword, comprises: determining that one or more particular phones occur in the transcription of the candidate hotword. | 11. The method of claim 1 , wherein evaluating the speech data, or a transcription of the candidate hotword, comprises: determining that one or more particular phones occur in the transcription of the candidate hotword. 13. The method of claim 11 , wherein the occurrence of the particular phones in the transcription is associated with a lower hotword suitability score. | 0.909797 |
8,037,071 | 1 | 7 | 1. A computer implemented method of searching for and presenting content items as an arrangement of one or more concept clusters to facilitate further search and navigation using at least one of a display-constrained display device and/or an input-constrained input device, the method comprising: accessing an electronically-readable storage medium containing a candidate set of content items; organizing at least some content items of the candidate set of content items into a hierarchical set of concept clusters, wherein at least two concept clusters in the hierarchical set of concept clusters each includes a respective set of content items, wherein the content items within each of the respective sets are related by one or more common themes or information types, and wherein at least one concept cluster in the hierarchical set of concept clusters has one or more cluster identifiers, and wherein at least one concept cluster in the hierarchical set of concept clusters is a parent cluster and comprises a child cluster; and receiving user input comprising more than one search term; identifying a concept cluster in the hierarchical set of concept clusters that has one or more cluster identifiers matching the user input, wherein the concept cluster in the hierarchical set of concept clusters having one or more cluster identifiers matching the user input is a parent cluster of a child cluster having a child cluster identifier; generating a flattened cluster based on a combination of the parent cluster in the hierarchical set of concept clusters having one or more cluster identifiers matching the user input and the child cluster of the parent cluster in the hierarchical set of concept clusters having one or more cluster identifiers matching the user input; and presenting the flattened cluster on the display device. | 1. A computer implemented method of searching for and presenting content items as an arrangement of one or more concept clusters to facilitate further search and navigation using at least one of a display-constrained display device and/or an input-constrained input device, the method comprising: accessing an electronically-readable storage medium containing a candidate set of content items; organizing at least some content items of the candidate set of content items into a hierarchical set of concept clusters, wherein at least two concept clusters in the hierarchical set of concept clusters each includes a respective set of content items, wherein the content items within each of the respective sets are related by one or more common themes or information types, and wherein at least one concept cluster in the hierarchical set of concept clusters has one or more cluster identifiers, and wherein at least one concept cluster in the hierarchical set of concept clusters is a parent cluster and comprises a child cluster; and receiving user input comprising more than one search term; identifying a concept cluster in the hierarchical set of concept clusters that has one or more cluster identifiers matching the user input, wherein the concept cluster in the hierarchical set of concept clusters having one or more cluster identifiers matching the user input is a parent cluster of a child cluster having a child cluster identifier; generating a flattened cluster based on a combination of the parent cluster in the hierarchical set of concept clusters having one or more cluster identifiers matching the user input and the child cluster of the parent cluster in the hierarchical set of concept clusters having one or more cluster identifiers matching the user input; and presenting the flattened cluster on the display device. 7. The method of claim 1 , wherein presenting the flattened cluster is based at least in part on a combination of the one or more cluster identifiers matching the user input and the child cluster identifier. | 0.794235 |
8,880,520 | 12 | 17 | 12. A method comprising: receiving, by a processor, a search query from a search user; classifying, by the processor, the search query into at least one query-class from a plurality of query-classes; performing, by the processor, a search using the search query over a plurality of non-trust data sources to obtain a plurality of non-trust search results; selectively performing, by the processor, another search using the search query over a plurality of identified trust data sources to obtain a plurality of trust search results, wherein the identified trust data sources include explicit trusted data sources that are trusted specifically by the search user and wherein the non-trust data sources are non-trusted specifically by the search user; categorizing, by the processor, the plurality of trust search results based on the search user's respective relationship with each identified trust data source, the search user's respective relationship being one from a group of relationships comprising an explicit trust data source relationship, an implicit trust data source relationship, and another trust data source relationship having a correspondence with a social networking source for which the search user is not a member; determining, by the processor and based on the at least one query-class for the search query and the trust search results categorization, a number and a position for selectively displaying each of the plurality of trust search results in a rank order; and selectively displaying, by the processor, the plurality of trust search results distinct from a display of the plurality of non-trust search results, wherein the selectively displayed plurality of trust search results is in accordance with the determination and includes display of information indicating an identified trust data source of each of the plurality of trust search results. | 12. A method comprising: receiving, by a processor, a search query from a search user; classifying, by the processor, the search query into at least one query-class from a plurality of query-classes; performing, by the processor, a search using the search query over a plurality of non-trust data sources to obtain a plurality of non-trust search results; selectively performing, by the processor, another search using the search query over a plurality of identified trust data sources to obtain a plurality of trust search results, wherein the identified trust data sources include explicit trusted data sources that are trusted specifically by the search user and wherein the non-trust data sources are non-trusted specifically by the search user; categorizing, by the processor, the plurality of trust search results based on the search user's respective relationship with each identified trust data source, the search user's respective relationship being one from a group of relationships comprising an explicit trust data source relationship, an implicit trust data source relationship, and another trust data source relationship having a correspondence with a social networking source for which the search user is not a member; determining, by the processor and based on the at least one query-class for the search query and the trust search results categorization, a number and a position for selectively displaying each of the plurality of trust search results in a rank order; and selectively displaying, by the processor, the plurality of trust search results distinct from a display of the plurality of non-trust search results, wherein the selectively displayed plurality of trust search results is in accordance with the determination and includes display of information indicating an identified trust data source of each of the plurality of trust search results. 17. The method of claim 12 , wherein the plurality of trust search results is sorted based on a defined number of updates of information provided for a given identified trust data source. | 0.919327 |
9,355,353 | 1 | 9 | 1. A method for aiding diagnosis of an object showing at least one disorder and for selecting a finding that characterizes at least part of the state of the object, the method comprising: storing a number of findings in at least one data base; wherein each of the stored findings is described by a severity of the finding and a symptom constellation of a number of symptoms and by a graphic representation of the symptom constellation, as a visual pathology, wherein each symptom shows at least one symptom type and at least one expression, and wherein each symptom in each pathology is represented by a symbol the coordinates of which are determined in a first dimension by the symptom type of the symptom and in a second dimension by expression of the symptom, wherein the expression is determined by a subjectively perceived significance in respect of the disorder-generating source; and wherein a dialog-based, visual modeling of the state of the object occurs to which end the state of the object is described by a current symptom constellation which may comprise multiple symptoms, wherein each symptom shows at least one symptom type and at least one expression, and wherein the current symptom constellation is represented as an object image wherein each symptom is represented by a symbol whose coordinates are Determined in a first dimension by the symptom type of the symptom and in a second dimension by the expression of the symptom; and wherein to aid diagnosis at least one computer, at least one comparator, at least one input device, and at least one display device are provided; wherein the following process steps are carried out: deriving a current symptom constellation from a pre-defined symptom constellation; deriving a current list of findings from a pre-defined list of findings containing stored findings; deriving a current list of suggestions for symptoms from a pre-defined list of suggested symptoms; and wherein the following process steps are automatically repeated in a loop in this or another suitable sequence until a finding is determined manually, or until a pathology and thus the pertaining finding is selected or until the process is abandoned: a) by way of the input device at least one symptom of the current symptom constellation is modified for modelling the state of the object and the modified symptom constellation is stored as the current symptom constellation and the current symptom constellation is automatically and immediately graphically output on the display device as the current object image; b) the comparator automatically compares, following each case of symptom modification, the current symptom constellation against the stored symptom constellations of the findings of the current list of findings and immediately deletes from the current list of findings those findings showing a congruence with the current symptom constellation that remains beneath a predetermined, first value; c) the comparator automatically compares, following each case of symptom modification, the current symptom constellation against the symptom constellations of the findings stored in the data base and immediately adds to the current list of findings those stored findings showing a congruence of the respective symptom constellation with the current symptom constellation that lies above a predetermined, second value; d) the comparator automatically compares the current symptom constellation against the symptom constellations of the findings stored in the data base and adds stored findings to the current list of findings if the congruence of the respective symptom constellation with the current symptom constellation remains below the predetermined, first value but lies above a predetermined, third value if the disorder potential of the stored finding exceeds a predetermined threshold; e) the current list of findings is automatically and immediately sorted by the computer following each case of symptom modification, which sorting takes into account the similarity of the current symptom constellation with the respective symptom constellation of the stored findings and the severity of the stored finding; f) the symptom constellation pertaining to at least one finding of the current list of findings is plotted on the display device as pathology if the current list of findings includes at least one finding; and g) the comparator compares, following each case of symptom modification, the current list of suggestions for symptoms against the symptoms of the findings of the current list of findings, and re-sorts the current list of suggestions, and immediately outputs the current list of suggestions. | 1. A method for aiding diagnosis of an object showing at least one disorder and for selecting a finding that characterizes at least part of the state of the object, the method comprising: storing a number of findings in at least one data base; wherein each of the stored findings is described by a severity of the finding and a symptom constellation of a number of symptoms and by a graphic representation of the symptom constellation, as a visual pathology, wherein each symptom shows at least one symptom type and at least one expression, and wherein each symptom in each pathology is represented by a symbol the coordinates of which are determined in a first dimension by the symptom type of the symptom and in a second dimension by expression of the symptom, wherein the expression is determined by a subjectively perceived significance in respect of the disorder-generating source; and wherein a dialog-based, visual modeling of the state of the object occurs to which end the state of the object is described by a current symptom constellation which may comprise multiple symptoms, wherein each symptom shows at least one symptom type and at least one expression, and wherein the current symptom constellation is represented as an object image wherein each symptom is represented by a symbol whose coordinates are Determined in a first dimension by the symptom type of the symptom and in a second dimension by the expression of the symptom; and wherein to aid diagnosis at least one computer, at least one comparator, at least one input device, and at least one display device are provided; wherein the following process steps are carried out: deriving a current symptom constellation from a pre-defined symptom constellation; deriving a current list of findings from a pre-defined list of findings containing stored findings; deriving a current list of suggestions for symptoms from a pre-defined list of suggested symptoms; and wherein the following process steps are automatically repeated in a loop in this or another suitable sequence until a finding is determined manually, or until a pathology and thus the pertaining finding is selected or until the process is abandoned: a) by way of the input device at least one symptom of the current symptom constellation is modified for modelling the state of the object and the modified symptom constellation is stored as the current symptom constellation and the current symptom constellation is automatically and immediately graphically output on the display device as the current object image; b) the comparator automatically compares, following each case of symptom modification, the current symptom constellation against the stored symptom constellations of the findings of the current list of findings and immediately deletes from the current list of findings those findings showing a congruence with the current symptom constellation that remains beneath a predetermined, first value; c) the comparator automatically compares, following each case of symptom modification, the current symptom constellation against the symptom constellations of the findings stored in the data base and immediately adds to the current list of findings those stored findings showing a congruence of the respective symptom constellation with the current symptom constellation that lies above a predetermined, second value; d) the comparator automatically compares the current symptom constellation against the symptom constellations of the findings stored in the data base and adds stored findings to the current list of findings if the congruence of the respective symptom constellation with the current symptom constellation remains below the predetermined, first value but lies above a predetermined, third value if the disorder potential of the stored finding exceeds a predetermined threshold; e) the current list of findings is automatically and immediately sorted by the computer following each case of symptom modification, which sorting takes into account the similarity of the current symptom constellation with the respective symptom constellation of the stored findings and the severity of the stored finding; f) the symptom constellation pertaining to at least one finding of the current list of findings is plotted on the display device as pathology if the current list of findings includes at least one finding; and g) the comparator compares, following each case of symptom modification, the current list of suggestions for symptoms against the symptoms of the findings of the current list of findings, and re-sorts the current list of suggestions, and immediately outputs the current list of suggestions. 9. The method according to claim 1 wherein negative symptoms can be specified. | 0.906699 |
7,509,330 | 24 | 34 | 24. A method for application-layer monitoring of communication between one or more database clients and one or more database servers, the method comprising: at a decoding layer above a network layer on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations: using one or more decoders on the database device for receiving database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decoding the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database serve; and extracting query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and at an application layer above the decoding layer at the first network location, using a monitoring application on the database device for receiving query-language statements extracted at the decoders and recording observations on the database messages based at least in part on the query-language statements extracted at the decoding layer. | 24. A method for application-layer monitoring of communication between one or more database clients and one or more database servers, the method comprising: at a decoding layer above a network layer on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations: using one or more decoders on the database device for receiving database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decoding the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database serve; and extracting query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and at an application layer above the decoding layer at the first network location, using a monitoring application on the database device for receiving query-language statements extracted at the decoders and recording observations on the database messages based at least in part on the query-language statements extracted at the decoding layer. 34. The method of claim 24 , further comprising, at the application layer, providing user access to recorded observations based at least in part on the querylanguage statements extracted at the decoding layer using a graphical user interface (GUI) comprising at least one or more of: a statistical display of recorded observations; a historical display of recorded observations; and a tabular display of recorded observations. | 0.87276 |
8,239,366 | 37 | 38 | 37. The at least one tangible computer-readable medium of claim 34 , wherein the act of generating further comprises: selecting one of a plurality of available language models to be used in performing automatic speech recognition on the voice input; and performing automatic speech recognition on the voice input using the selected one of the plurality of language models. | 37. The at least one tangible computer-readable medium of claim 34 , wherein the act of generating further comprises: selecting one of a plurality of available language models to be used in performing automatic speech recognition on the voice input; and performing automatic speech recognition on the voice input using the selected one of the plurality of language models. 38. The at least one tangible computer-readable medium of claim 37 , wherein the act of selecting further comprises: selecting the one of a plurality of available language models to be used in performing automatic speech recognition on the voice input based, at least in part, on the content of the voice input. | 0.924109 |
7,526,424 | 1 | 31 | 1. A sentence realization system for processing an abstract linguistic representation (ALR) of a sentence into a structure that can be fully realized, comprising: a tree conversion component configured for receiving the ALR and generating a basic syntax tree from the ALR, the basic syntax tree including parent and child nodes, the parent nodes being ancestor nodes to the child nodes; a global movement component configured for receiving the basic syntax tree and hierarchically ordering child nodes relative to ancestor nodes to obtain a hierarchically ordered tree; an intra-constituent ordering component configured for receiving the hierarchically ordered tree and establishing a linear order among the nodes in the hierarchically ordered tree to obtain a fully ordered tree; a surface clean-up component configured for receiving the fully ordered tree and generating surface realizations for constituents in the fully ordered tree that are to be realized but are as yet abstract, to obtain a cleaned tree; and a surface realization component configured for outputting a text based at least in part on the cleaned tree; wherein one or more of the components comprises a decision tree classifier. | 1. A sentence realization system for processing an abstract linguistic representation (ALR) of a sentence into a structure that can be fully realized, comprising: a tree conversion component configured for receiving the ALR and generating a basic syntax tree from the ALR, the basic syntax tree including parent and child nodes, the parent nodes being ancestor nodes to the child nodes; a global movement component configured for receiving the basic syntax tree and hierarchically ordering child nodes relative to ancestor nodes to obtain a hierarchically ordered tree; an intra-constituent ordering component configured for receiving the hierarchically ordered tree and establishing a linear order among the nodes in the hierarchically ordered tree to obtain a fully ordered tree; a surface clean-up component configured for receiving the fully ordered tree and generating surface realizations for constituents in the fully ordered tree that are to be realized but are as yet abstract, to obtain a cleaned tree; and a surface realization component configured for outputting a text based at least in part on the cleaned tree; wherein one or more of the components comprises a decision tree classifier. 31. The system of claim 1 wherein the intra-constituent ordering component is configured to traverse the hierarchically ordered tree by selecting a parent node and linearly ordering each child node in the hierarchically ordered tree relative to other child nodes that have the selected parent node. | 0.501672 |
7,827,165 | 1 | 13 | 1. A method, in a data processing system, for communication within a digital social network using a social network input dictionary, comprising: monitoring communications within the digital social network to identify a term used by one or more members of the digital social network, the digital social network being a plurality of members who are associated with one another via one of a centralized or distributed digital social network provider system; measuring a usage of the term by the one or more members of the digital social network; determining if the term is present in a social network input dictionary for the digital social network; determining if the measured usage of the term by the one or more members of the digital social network meets a criteria for addition of the term to the social network input dictionary; adding the term to the social network input dictionary for the digital social network if the term is not already present in the social network input dictionary and the measured usage of the term meets the criteria; and utilizing the social network input dictionary to generate textual representations of messages input by one or more of the members of the digital social network, wherein the social network input dictionary comprises general terms and digital social network specific terms, wherein utilizing the social network input dictionary to generate textual representations of messages input by one or more of the members of the digital social network comprises: receiving user input from a member of the plurality of members, the user input specifying a message to be communicated to a recipient; comparing the user input to the social network input dictionary to match portions of the user input to terms in the social network input dictionary; using the matched terms to generate a textual representation of the user input; identifying the recipient of the message to be communicated; and determining if the recipient is a member of the plurality of members of the digital social network, and wherein comparing the user input to the social network input dictionary comprises: using only general terms for matching with portions of the user input if the recipient is not a member of the plurality of members of the digital social network; and using both the general terms and the digital social network specific terms for matching with portions of the user input if the recipient is a member of the plurality of members of the digital social network. | 1. A method, in a data processing system, for communication within a digital social network using a social network input dictionary, comprising: monitoring communications within the digital social network to identify a term used by one or more members of the digital social network, the digital social network being a plurality of members who are associated with one another via one of a centralized or distributed digital social network provider system; measuring a usage of the term by the one or more members of the digital social network; determining if the term is present in a social network input dictionary for the digital social network; determining if the measured usage of the term by the one or more members of the digital social network meets a criteria for addition of the term to the social network input dictionary; adding the term to the social network input dictionary for the digital social network if the term is not already present in the social network input dictionary and the measured usage of the term meets the criteria; and utilizing the social network input dictionary to generate textual representations of messages input by one or more of the members of the digital social network, wherein the social network input dictionary comprises general terms and digital social network specific terms, wherein utilizing the social network input dictionary to generate textual representations of messages input by one or more of the members of the digital social network comprises: receiving user input from a member of the plurality of members, the user input specifying a message to be communicated to a recipient; comparing the user input to the social network input dictionary to match portions of the user input to terms in the social network input dictionary; using the matched terms to generate a textual representation of the user input; identifying the recipient of the message to be communicated; and determining if the recipient is a member of the plurality of members of the digital social network, and wherein comparing the user input to the social network input dictionary comprises: using only general terms for matching with portions of the user input if the recipient is not a member of the plurality of members of the digital social network; and using both the general terms and the digital social network specific terms for matching with portions of the user input if the recipient is a member of the plurality of members of the digital social network. 13. The method of claim 1 , wherein the communications that are monitored are communications between mobile electronic devices used by the plurality of members. | 0.863014 |
9,390,197 | 23 | 24 | 23. A method comprising: receiving first activity information for a sender of a message sent to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a first recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the first recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the first recipient; determining a category for the first link as a first category type; identifying a first edge between the first and second nodes is representative of the first category type; and in the social graph, updating a value of the first edge between the first and second nodes, wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises: extracting a user identifier from a cookie received with the first activity data; and if a match for the user identifier is not found in the social graph, performing a probabilistic fingerprinting approach using attributes comprising at least one of device identifiers; IP addresses; operating systems; browser types; browser versions; or user navigational, geo-temporal, and behavioral patterns. | 23. A method comprising: receiving first activity information for a sender of a message sent to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a first recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the first recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the first recipient; determining a category for the first link as a first category type; identifying a first edge between the first and second nodes is representative of the first category type; and in the social graph, updating a value of the first edge between the first and second nodes, wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises: extracting a user identifier from a cookie received with the first activity data; and if a match for the user identifier is not found in the social graph, performing a probabilistic fingerprinting approach using attributes comprising at least one of device identifiers; IP addresses; operating systems; browser types; browser versions; or user navigational, geo-temporal, and behavioral patterns. 24. The method of claim 23 wherein a personally identifiable information of the sender includes an e-mail address of the sender. | 0.884058 |
7,801,909 | 68 | 80 | 68. A computer-implemented method for analyzing potential patent infringement, comprising: receiving information regarding a patent; processing the information regarding the patent; identifying a claim of the patent; formulating a search query containing terms in the claim and a foreign language translation of at least one of the terms; automatically generating a natural language question for use in obtaining information from a chat room or an on-line bulletin board; transmitting the natural language question to the chat room or the on-line bulletin board; in response to the question, obtaining information regarding at least one of a product, products, a service, and services from the chat room or the on-line bulletin board; searching the information regarding at least one of a product, products, a service, and services using the query; generating claim chart information containing at least some of the information regarding the at least one of a product, products, a service, and services; and transmitting the claim chart information to a user communication device in order to display the claim chart information to a user. | 68. A computer-implemented method for analyzing potential patent infringement, comprising: receiving information regarding a patent; processing the information regarding the patent; identifying a claim of the patent; formulating a search query containing terms in the claim and a foreign language translation of at least one of the terms; automatically generating a natural language question for use in obtaining information from a chat room or an on-line bulletin board; transmitting the natural language question to the chat room or the on-line bulletin board; in response to the question, obtaining information regarding at least one of a product, products, a service, and services from the chat room or the on-line bulletin board; searching the information regarding at least one of a product, products, a service, and services using the query; generating claim chart information containing at least some of the information regarding the at least one of a product, products, a service, and services; and transmitting the claim chart information to a user communication device in order to display the claim chart information to a user. 80. The method of claim 68 , wherein the step of generating claim chart information comprises: generating the claim chart information in a plurality of languages. | 0.793367 |
8,234,560 | 16 | 23 | 16. A computer-program product for use in conjunction with a computer system, the computer-program product comprising a computer-readable storage medium and a computer-program mechanism embedded therein for configuring the computer system to create documents in a hierarchy, the computer-program mechanism including: instructions for generating a root number which corresponds to a base level in the hierarchy; instructions for assigning document numbers to the documents, wherein the document numbers are generated based at least in part on the root number; instructions for assigning directory numbers to directories in the hierarchy, wherein a given directory number is generated based at least in part on a given document number, and wherein a given directory is in a branch that is coupled to the root level; instructions for determining paths in the hierarchy corresponding to the document numbers and the directory numbers, wherein a given path includes the base level and zero or more dependent branches; instructions for generating content numbers for the documents based at least in part on the corresponding paths through the hierarchy; instructions for creating the documents, wherein creating the documents comprises translating a content number for each document to determine content to be placed within the document; and instructions for storing, in a memory, the created documents in the directories in the hierarchy. | 16. A computer-program product for use in conjunction with a computer system, the computer-program product comprising a computer-readable storage medium and a computer-program mechanism embedded therein for configuring the computer system to create documents in a hierarchy, the computer-program mechanism including: instructions for generating a root number which corresponds to a base level in the hierarchy; instructions for assigning document numbers to the documents, wherein the document numbers are generated based at least in part on the root number; instructions for assigning directory numbers to directories in the hierarchy, wherein a given directory number is generated based at least in part on a given document number, and wherein a given directory is in a branch that is coupled to the root level; instructions for determining paths in the hierarchy corresponding to the document numbers and the directory numbers, wherein a given path includes the base level and zero or more dependent branches; instructions for generating content numbers for the documents based at least in part on the corresponding paths through the hierarchy; instructions for creating the documents, wherein creating the documents comprises translating a content number for each document to determine content to be placed within the document; and instructions for storing, in a memory, the created documents in the directories in the hierarchy. 23. The computer-program product of claim 16 , further comprising adding punctuation marks to the documents based at least in part on one or more factors of the content numbers. | 0.715434 |
8,515,999 | 5 | 6 | 5. The method of claim 1 , where validating comprises querying a facts database. | 5. The method of claim 1 , where validating comprises querying a facts database. 6. The method of claim 5 , where an output of the facts database is expressed as a facts XML instance. | 0.968538 |
7,630,947 | 1 | 3 | 1. A method for use of a medical ontology for computer assisted clinical decision support, the method comprising: identifying, with a processor of a data mining system, a plurality of associated terms from a medical ontology; generating, with the processor of the data mining system, a domain-knowledge base from the associated terms; and mining, with the data mining system, a medical record as a function of the domain-knowledge base. | 1. A method for use of a medical ontology for computer assisted clinical decision support, the method comprising: identifying, with a processor of a data mining system, a plurality of associated terms from a medical ontology; generating, with the processor of the data mining system, a domain-knowledge base from the associated terms; and mining, with the data mining system, a medical record as a function of the domain-knowledge base. 3. The method of claim 1 wherein identifying comprises identifying at least some of the associated terms as causes, effects, symptoms, signs, related diseases, body locations, morphology, or combinations thereof of a disease. | 0.691781 |
7,769,739 | 1 | 7 | 1. A method, comprising: providing, by a computer, a search interface comprising an accessing application search parameter field and a file type search parameter field, wherein the search interface allows an accessing application search parameter and a file type search parameter to be specified separately, and wherein the search interface allows both the accessing application search parameter and the file type search parameter to be specified for a search query; receiving a search query via the provided search interface to perform a search for an item, the search query comprising at least an indication of an accessing application; searching for the item using the search query including the indication of the accessing application, wherein said searching for the item comprises: selecting a list of items, from among a plurality of lists of items, wherein the selected list comprises a listing of items accessed by the accessing application as indicated in the received search query, wherein each of the plurality of lists of items corresponds to a different accessing application, and each list comprises a listing of items accessed by its respective accessing application; and parsing the selected list of items to find one or more items that correspond to the received search query; and presenting, by the computer, a search result based on the parsing. | 1. A method, comprising: providing, by a computer, a search interface comprising an accessing application search parameter field and a file type search parameter field, wherein the search interface allows an accessing application search parameter and a file type search parameter to be specified separately, and wherein the search interface allows both the accessing application search parameter and the file type search parameter to be specified for a search query; receiving a search query via the provided search interface to perform a search for an item, the search query comprising at least an indication of an accessing application; searching for the item using the search query including the indication of the accessing application, wherein said searching for the item comprises: selecting a list of items, from among a plurality of lists of items, wherein the selected list comprises a listing of items accessed by the accessing application as indicated in the received search query, wherein each of the plurality of lists of items corresponds to a different accessing application, and each list comprises a listing of items accessed by its respective accessing application; and parsing the selected list of items to find one or more items that correspond to the received search query; and presenting, by the computer, a search result based on the parsing. 7. The method of claim 1 , wherein the item comprises a file. | 0.870763 |
7,856,472 | 73 | 86 | 73. The computer program product of claim 72 , and further comprising computer code for displaying, in response to a first user interaction, the first additional information associated with the first message, utilizing the at least one window. | 73. The computer program product of claim 72 , and further comprising computer code for displaying, in response to a first user interaction, the first additional information associated with the first message, utilizing the at least one window. 86. The computer program product of claim 73 , wherein the computer program product is configured such that the first message includes the first additional information. | 0.9625 |
9,251,275 | 1 | 3 | 1. A method for data clustering and user modeling for next-best-action decisions, the method comprising the computer-implemented steps of: receiving unstructured social data of a plurality of users, the unstructured social data comprising one or more indicators including a set of words located in the unstructured social data that indicate at least one of: sentiment, personality, and emotional state; analyzing the unstructured social data of each user of the plurality of users to assign a numerical value to each of a plurality of feature vectors to associate with each of the plurality of users based on the set of words of the one or more indicators located in the unstructured social data generated by the user, each of the set of feature vectors corresponding to one or more personality characteristics that include a learning style, a propensity to purchase, a socioeconomic class, and a personality trait of each of the plurality of users; analyzing the set of feature vectors to identify two or more users from the plurality of users sharing a set of similar feature vectors; grouping the two or more users from the plurality of users sharing the set of similar feature vectors to form a cluster; identifying attributes of the cluster based on the feature vectors of the users grouped in the cluster; and inputting the attributes of the cluster into a predictive model to automatically determine a commercial offer that corresponds to the cluster. | 1. A method for data clustering and user modeling for next-best-action decisions, the method comprising the computer-implemented steps of: receiving unstructured social data of a plurality of users, the unstructured social data comprising one or more indicators including a set of words located in the unstructured social data that indicate at least one of: sentiment, personality, and emotional state; analyzing the unstructured social data of each user of the plurality of users to assign a numerical value to each of a plurality of feature vectors to associate with each of the plurality of users based on the set of words of the one or more indicators located in the unstructured social data generated by the user, each of the set of feature vectors corresponding to one or more personality characteristics that include a learning style, a propensity to purchase, a socioeconomic class, and a personality trait of each of the plurality of users; analyzing the set of feature vectors to identify two or more users from the plurality of users sharing a set of similar feature vectors; grouping the two or more users from the plurality of users sharing the set of similar feature vectors to form a cluster; identifying attributes of the cluster based on the feature vectors of the users grouped in the cluster; and inputting the attributes of the cluster into a predictive model to automatically determine a commercial offer that corresponds to the cluster. 3. The method according to claim 1 , further comprising receiving structured data of the plurality of users. | 0.944272 |
8,082,241 | 1 | 3 | 1. A computer-based method for processing one or more citations within a document, the method comprising: scanning a document to identify an unformatted citation; parsing the unformatted citation to determine one or more citation terms; querying one or more citation libraries to find possible citations, each possible citation comprising at least a portion of the one or more citation terms; selecting one of the possible citations; and inserting a formatted citation based on the selected one of the possible citations into the document. | 1. A computer-based method for processing one or more citations within a document, the method comprising: scanning a document to identify an unformatted citation; parsing the unformatted citation to determine one or more citation terms; querying one or more citation libraries to find possible citations, each possible citation comprising at least a portion of the one or more citation terms; selecting one of the possible citations; and inserting a formatted citation based on the selected one of the possible citations into the document. 3. The method of claim 1 wherein scanning is executed when an idle state is identified. | 0.86976 |
9,792,361 | 1 | 12 | 1. A computer implemented system for presenting social network provided outputs to a mobile electronic device dependent on a location, in response to the mobile electronic device user's input, comprising: a hardware data input port configured to receive information from the mobile electronic device user defining the user input; an automated hardware processor configured to define a user request dependent on the user input and metadata associated with the received information from the mobile electronic device user, comprising at least the location of the mobile electronic device determined by an automated hardware geospatial positioning system; an automated hardware communication interface port configured to: automatically transmit the user request to a social network database comprising a plurality of roadway condition records having time information and location information associated with respective roadway conditions; automatically receive location-dependent social network information from the social network database, selectively dependent on the transmitted user request; and communicate a message dependent on the received location-dependent social network information for creating a new record in the social network database, comprising time information and location information of a respective roadway condition; an automated hardware user interface configured to selectively present the received social network information ranked according to at least one social network ranking factor. | 1. A computer implemented system for presenting social network provided outputs to a mobile electronic device dependent on a location, in response to the mobile electronic device user's input, comprising: a hardware data input port configured to receive information from the mobile electronic device user defining the user input; an automated hardware processor configured to define a user request dependent on the user input and metadata associated with the received information from the mobile electronic device user, comprising at least the location of the mobile electronic device determined by an automated hardware geospatial positioning system; an automated hardware communication interface port configured to: automatically transmit the user request to a social network database comprising a plurality of roadway condition records having time information and location information associated with respective roadway conditions; automatically receive location-dependent social network information from the social network database, selectively dependent on the transmitted user request; and communicate a message dependent on the received location-dependent social network information for creating a new record in the social network database, comprising time information and location information of a respective roadway condition; an automated hardware user interface configured to selectively present the received social network information ranked according to at least one social network ranking factor. 12. The computer implemented system according to claim 1 , wherein the automated hardware user interface comprises a geographic map. | 0.874525 |
9,552,562 | 1 | 4 | 1. A method comprising: receiving a request to launch a visual information builder for a specific task of an application that uses a rule engine; accessing a stored rule model of two or more different candidate rule models, wherein the rule model comprises a plurality of objects including nodes and attributes wherein the nodes correspond to conditions and actions and wherein the attributes comprise parameters for defining the conditions and actions; wherein the plurality of objects are retrieved from a rule dictionary of the rule engine based on the specific task; wherein a particular node of the plurality of objects is associated with a template defining one or more options, for the particular node, that are based on the specific task; presenting a user interface of the visual information builder that is configured to receive user input specifying a selection of one or more objects from the rule model and specifying a logical combination of the one or more objects that were selected from the rule model, wherein the particular node is editable in the user interface according to the template; receiving user input specifying one or more selected objects and a particular logical combination of the one or more selected objects; converting the particular logical combination of the one or more selected objects into one or more rules evaluable by the rule engine; and storing the one or more rules in the rule dictionary; wherein the method is performed by one or more computing devices. | 1. A method comprising: receiving a request to launch a visual information builder for a specific task of an application that uses a rule engine; accessing a stored rule model of two or more different candidate rule models, wherein the rule model comprises a plurality of objects including nodes and attributes wherein the nodes correspond to conditions and actions and wherein the attributes comprise parameters for defining the conditions and actions; wherein the plurality of objects are retrieved from a rule dictionary of the rule engine based on the specific task; wherein a particular node of the plurality of objects is associated with a template defining one or more options, for the particular node, that are based on the specific task; presenting a user interface of the visual information builder that is configured to receive user input specifying a selection of one or more objects from the rule model and specifying a logical combination of the one or more objects that were selected from the rule model, wherein the particular node is editable in the user interface according to the template; receiving user input specifying one or more selected objects and a particular logical combination of the one or more selected objects; converting the particular logical combination of the one or more selected objects into one or more rules evaluable by the rule engine; and storing the one or more rules in the rule dictionary; wherein the method is performed by one or more computing devices. 4. The method of claim 1 , wherein the template is custom for the particular object. | 0.861386 |
8,195,772 | 14 | 20 | 14. A method according to claim 3 , comprising overriding at least one automatically generated customization definition by said user. | 14. A method according to claim 3 , comprising overriding at least one automatically generated customization definition by said user. 20. A method according to claim 14 , wherein said overriding comprises allowing a match other than a one-to-one match to a definition, for a customization to be applied. | 0.942439 |
8,812,593 | 1 | 2 | 1. A computer-implemented method for managing users of a community-based content aggregation environment, the method comprising: creating, by a processor device executing code stored on a non-transitory computer-readable storage medium, a user profile for a user providing a registration request; assigning a first user level to the user, the first user level corresponding to access to a first set of community tools; detecting user activity, wherein user activity comprises receiving an element from the user comprising content related to a community topic or receiving element attributes from the user comprising a comment, a rating, or a label identifying a sub-topic of the community topic; providing the element or the element attributes to a moderator, wherein the moderator is at least one user that is charged with approving elements or element attributes; receiving an instruction from the moderator to approve the element or the element attributes; determining points to award to the user based on the approval of the element or the element attributes by the moderator; storing the points in the user profile; determining that points in the user profile exceed a pre-set threshold; and modifying the first user level to a second user level based on determining that points in the user profile exceed the pre-set threshold, the second user level allowing the user to access the first set of community tools and a second set of community tools. | 1. A computer-implemented method for managing users of a community-based content aggregation environment, the method comprising: creating, by a processor device executing code stored on a non-transitory computer-readable storage medium, a user profile for a user providing a registration request; assigning a first user level to the user, the first user level corresponding to access to a first set of community tools; detecting user activity, wherein user activity comprises receiving an element from the user comprising content related to a community topic or receiving element attributes from the user comprising a comment, a rating, or a label identifying a sub-topic of the community topic; providing the element or the element attributes to a moderator, wherein the moderator is at least one user that is charged with approving elements or element attributes; receiving an instruction from the moderator to approve the element or the element attributes; determining points to award to the user based on the approval of the element or the element attributes by the moderator; storing the points in the user profile; determining that points in the user profile exceed a pre-set threshold; and modifying the first user level to a second user level based on determining that points in the user profile exceed the pre-set threshold, the second user level allowing the user to access the first set of community tools and a second set of community tools. 2. The computer-implemented method of claim 1 , wherein the second user level is assigned to the moderator. | 0.897706 |
8,606,804 | 15 | 16 | 15. A computer-readable storage device storing computer-executable instructions that, when executed by a server computer, cause the server computer to perform a method, comprising: providing, on the server computer, a programming model for providing a web service that supports defining a concrete custom query builder subclass derived from a query builder base class included in the programming model and defining a concrete arguments class that extends an arguments base class included in the programming model, wherein: the query builder base class is configured to use query parameters of the arguments base class to create queries; the concrete arguments class includes one or more custom query parameters specific to the concrete custom query builder subclass; the concrete custom query builder subclass is configured to dynamically create a custom query at runtime using parameter values of the one or more custom query parameters which are to be bound to the concrete custom query builder subclass at runtime; the concrete custom query builder subclass uses the custom query to dynamically create a query run at runtime, wherein the query run is configured to execute the custom query for returning query results based on the one or more custom query parameters; and the query builder base class includes a method for initializing an instance of the custom query builder subclass at runtime and a method for retrieving the query run created by the concrete query builder subclass; providing, on the server computer, a query service that provides an interface to expose data access functionality via the query builder base class included in the programming model; accepting, by the query service from a consumer application at runtime, a query request that includes a reference to the concrete custom query builder subclass; invoking, by the query service, the concrete custom query builder subclass to initialize the instance of the concrete custom query builder subclass and retrieve the query run created by the concrete custom query builder subclass; executing, by the query service, the query run created by the concrete custom query builder subclass for retrieving the query results based on the one or more custom query parameters; and returning, by the query service, the query results to the consumer application at runtime. | 15. A computer-readable storage device storing computer-executable instructions that, when executed by a server computer, cause the server computer to perform a method, comprising: providing, on the server computer, a programming model for providing a web service that supports defining a concrete custom query builder subclass derived from a query builder base class included in the programming model and defining a concrete arguments class that extends an arguments base class included in the programming model, wherein: the query builder base class is configured to use query parameters of the arguments base class to create queries; the concrete arguments class includes one or more custom query parameters specific to the concrete custom query builder subclass; the concrete custom query builder subclass is configured to dynamically create a custom query at runtime using parameter values of the one or more custom query parameters which are to be bound to the concrete custom query builder subclass at runtime; the concrete custom query builder subclass uses the custom query to dynamically create a query run at runtime, wherein the query run is configured to execute the custom query for returning query results based on the one or more custom query parameters; and the query builder base class includes a method for initializing an instance of the custom query builder subclass at runtime and a method for retrieving the query run created by the concrete query builder subclass; providing, on the server computer, a query service that provides an interface to expose data access functionality via the query builder base class included in the programming model; accepting, by the query service from a consumer application at runtime, a query request that includes a reference to the concrete custom query builder subclass; invoking, by the query service, the concrete custom query builder subclass to initialize the instance of the concrete custom query builder subclass and retrieve the query run created by the concrete custom query builder subclass; executing, by the query service, the query run created by the concrete custom query builder subclass for retrieving the query results based on the one or more custom query parameters; and returning, by the query service, the query results to the consumer application at runtime. 16. The computer-readable storage device of claim 15 , further storing computer-executable instructions for: accepting, by the query service, one or more paging parameters for specifying a record limit for the query results. | 0.531381 |
9,595,171 | 20 | 22 | 20. The system of claim 13 , wherein the processor is further configured for: receiving a second plurality of candidate inputs from the sensor; classifying the second plurality of candidate inputs as one or more second intentional inputs; and determining a command for controlling the target device based on the one or more second intentional inputs, wherein providing the signal to the selected target device comprises providing a signal indicative of the command to the selected target device in response to the intentional input. | 20. The system of claim 13 , wherein the processor is further configured for: receiving a second plurality of candidate inputs from the sensor; classifying the second plurality of candidate inputs as one or more second intentional inputs; and determining a command for controlling the target device based on the one or more second intentional inputs, wherein providing the signal to the selected target device comprises providing a signal indicative of the command to the selected target device in response to the intentional input. 22. The system of claim 20 , wherein the command is determined based on a number of the one or more second intentional inputs received during a time window. | 0.958533 |
10,120,885 | 10 | 14 | 10. A method comprising: receiving a data definition statement involving a modification to a database object, the data definition statement including a clause imposing a restriction on the modification to the database object based on whether the modification results in invalidation of at least one dependent database object of the database object; in response to the clause being included in the received data definition statement, determining, using one or more processors of a machine, whether the modification results in invalidation of at least one dependent database object, the at least one dependent database object being dependent on the database object, the determining of whether the modification results in the invalidation of the at least one dependent database object includes determining whether the at least one dependent database object is able to be successfully recompiled as a result of the modification; based on determining that the modification results in the invalidation of at least one dependent database object, preventing the modification to the database object. | 10. A method comprising: receiving a data definition statement involving a modification to a database object, the data definition statement including a clause imposing a restriction on the modification to the database object based on whether the modification results in invalidation of at least one dependent database object of the database object; in response to the clause being included in the received data definition statement, determining, using one or more processors of a machine, whether the modification results in invalidation of at least one dependent database object, the at least one dependent database object being dependent on the database object, the determining of whether the modification results in the invalidation of the at least one dependent database object includes determining whether the at least one dependent database object is able to be successfully recompiled as a result of the modification; based on determining that the modification results in the invalidation of at least one dependent database object, preventing the modification to the database object. 14. The method of claim 10 , wherein the determining whether the modification results in the invalidation of at least one dependent database object further includes: identifying one or more dependent database objects with dependence on the database object. | 0.79187 |
9,098,567 | 14 | 15 | 14. An apparatus to determine a document rank, the apparatus comprising: a processor, a term relationship score calculating unit, a term relationship score changing unit, a contribution score calculating unit, and a document rank score calculating unit, the processor to control the term relationship score calculating unit, the term relationship score changing unit, the contribution score calculating unit, and the document rank score calculating unit, wherein the term relationship score calculating unit is configured to calculate a first term relationship score of a first document and a second term relationship score, and wherein the contribution score calculating unit is configured to calculate a first contribution score based on a common keyword between the first document and a second document, the second document being linked by a link to the first document, wherein the term relationship score changing unit is configured to change the first term relationship score to the second term relationship score, wherein the document rank score calculating unit is configured to calculate a document rank score of the second document based on the first term relationship score and the first contribution score, and to update the document rank score of the second document based on the second term relationship score, wherein the first term relationship score is determined based on content of the first document and the link, and wherein the processor is further configured to determine whether each of a plurality of contribution scores is greater than a predetermined threshold value to update the document rank score, whereby if one of the contribution scores is less than or equal to the predetermined threshold value, that contribution score is set to a zero value. | 14. An apparatus to determine a document rank, the apparatus comprising: a processor, a term relationship score calculating unit, a term relationship score changing unit, a contribution score calculating unit, and a document rank score calculating unit, the processor to control the term relationship score calculating unit, the term relationship score changing unit, the contribution score calculating unit, and the document rank score calculating unit, wherein the term relationship score calculating unit is configured to calculate a first term relationship score of a first document and a second term relationship score, and wherein the contribution score calculating unit is configured to calculate a first contribution score based on a common keyword between the first document and a second document, the second document being linked by a link to the first document, wherein the term relationship score changing unit is configured to change the first term relationship score to the second term relationship score, wherein the document rank score calculating unit is configured to calculate a document rank score of the second document based on the first term relationship score and the first contribution score, and to update the document rank score of the second document based on the second term relationship score, wherein the first term relationship score is determined based on content of the first document and the link, and wherein the processor is further configured to determine whether each of a plurality of contribution scores is greater than a predetermined threshold value to update the document rank score, whereby if one of the contribution scores is less than or equal to the predetermined threshold value, that contribution score is set to a zero value. 15. The apparatus of claim 14 , further comprising: a contribution coefficient calculating unit to calculate a first contribution coefficient and a second contribution coefficient based on the common keyword; and a contribution score calculating unit to calculate the first contribution score based on the first contribution coefficient and the first term relationship score of the first document, and to calculate a second contribution score based on the first contribution coefficient, the first term relationship score, the second contribution coefficient, and the second term relationship score, wherein the document rank score calculating unit is configured to calculate the document rank score of the second document based on the first term relationship score and the first contribution score with respect to the common keyword, and is configured to update the document rank score of the second document based on the second term relationship score and the second contribution score. | 0.500506 |
8,330,844 | 1 | 5 | 1. A non-transitory computer readable medium storing an application that when executed by at least one processor implements a graphical user interface (“GUI”), the GUI comprising: a first display area for displaying different groups of images imported in the application during different import sessions; a photo album tool comprising a second display area for associating different sets of images from the first display area with different digital photo albums and displaying each particular digital photo album as a user selectable item, wherein a selection of a selectable item corresponding to a particular digital photo album causes the first display area to only display a set of images associated with the particular digital photo album, wherein the first display area displays all the images imported in the application when no selectable item corresponding to a digital album is selected; an image set grouping tool that when selected causes the images in the first display area to be grouped into the different groups according to the different import sessions by displaying a group divider icon between each of two different groups of images; and a set of editing tools comprising a redeye removal tool for removing redeye from a particular image selected from the first display area. | 1. A non-transitory computer readable medium storing an application that when executed by at least one processor implements a graphical user interface (“GUI”), the GUI comprising: a first display area for displaying different groups of images imported in the application during different import sessions; a photo album tool comprising a second display area for associating different sets of images from the first display area with different digital photo albums and displaying each particular digital photo album as a user selectable item, wherein a selection of a selectable item corresponding to a particular digital photo album causes the first display area to only display a set of images associated with the particular digital photo album, wherein the first display area displays all the images imported in the application when no selectable item corresponding to a digital album is selected; an image set grouping tool that when selected causes the images in the first display area to be grouped into the different groups according to the different import sessions by displaying a group divider icon between each of two different groups of images; and a set of editing tools comprising a redeye removal tool for removing redeye from a particular image selected from the first display area. 5. The non-transitory computer readable medium of claim 1 , wherein the GUI further comprises a slide show tool, wherein a user's selection of the particular digital photo album and the slide show tool causes a slide show presentation comprising the set of images in the particular digital photo album to be displayed. | 0.747218 |
9,460,195 | 7 | 11 | 7. A computer-implemented method for determining term importance in a text content for information discovery and presentation, comprising: receiving a text content; tokenizing the text content into tokens as instances of terms, each token or term comprising one or more words or phrases; identifying a term with multiple token instances in the text content; identifying a first token instance of the term, wherein the first token instance is or is contained in a grammatical subject of a sentence; assigning a first importance value to the first token instance for being or being contained in a grammatical subject of a sentence; identifying a second token instance of the term, wherein the second token instance is or is in a non-subject portion of a sentence; assigning a second importance value to the second token instance for not being or not being contained in a grammatical subject of a sentence, wherein the second importance value is different from the first importance value; determining an importance measure for the term based on the sum of the first importance value and the second importance value; performing an action associated with the term if the importance measure is above a threshold, wherein the action comprises at least outputting an element associated with the term, displaying an element associated with the term, or using an element associated with the term for a computer-assisted operation associated with the text content including ranking a search result, wherein the element is selected from the group of elements consisting of at least the term, the importance measure, and a sentence or paragraph containing the term. | 7. A computer-implemented method for determining term importance in a text content for information discovery and presentation, comprising: receiving a text content; tokenizing the text content into tokens as instances of terms, each token or term comprising one or more words or phrases; identifying a term with multiple token instances in the text content; identifying a first token instance of the term, wherein the first token instance is or is contained in a grammatical subject of a sentence; assigning a first importance value to the first token instance for being or being contained in a grammatical subject of a sentence; identifying a second token instance of the term, wherein the second token instance is or is in a non-subject portion of a sentence; assigning a second importance value to the second token instance for not being or not being contained in a grammatical subject of a sentence, wherein the second importance value is different from the first importance value; determining an importance measure for the term based on the sum of the first importance value and the second importance value; performing an action associated with the term if the importance measure is above a threshold, wherein the action comprises at least outputting an element associated with the term, displaying an element associated with the term, or using an element associated with the term for a computer-assisted operation associated with the text content including ranking a search result, wherein the element is selected from the group of elements consisting of at least the term, the importance measure, and a sentence or paragraph containing the term. 11. The method of claim 7 , when the text content is made searchable, or is associated with a search index, the method further comprising: receiving a search query comprising a keyword; matching the keyword with the first term; returning the text content as a search result or part of a search result; and ranking the search result based at least on the first term importance measure or the second term importance measure. | 0.825186 |
8,423,546 | 6 | 7 | 6. The method as recited in claim 1 , wherein the act of selecting a specified number of key textual phrases comprises an act of using a weighting function to weight the statistical significance of the different textual phrases contained in the list relative to one another. | 6. The method as recited in claim 1 , wherein the act of selecting a specified number of key textual phrases comprises an act of using a weighting function to weight the statistical significance of the different textual phrases contained in the list relative to one another. 7. The method as recited in claim 6 , wherein the weighting function considers for each of the textual phrases in said list: the frequency of occurrence of the textual phrase within the document, an inverse document frequency for the textual phrase within a corpus of documents including the document, the language model, and the length of the document. | 0.910949 |
10,095,748 | 1 | 4 | 1. A method of personalizing query suggestions, comprising: receiving a query via computer-enabled query application; determining a first score for each of one or more people, wherein the first score is based on a frequency with which a querying user has selected each of the one or more people from previous query suggestions produced by the query application; determining a second score for each of the one or more people based on interactions between the querying user and the one or more people in one or more applications other than the query application; combining the first score and the second score to form a combined score, wherein the second score contributes less than the first score to the combined score; ranking each of the one or more people based on the combined score; providing, based on the ranking, a people query suggestion in a query suggestion user interface; and providing an actor-action query suggestion in the query suggestion user interface for receiving information about a content item action associated with a person corresponding to the content item action. | 1. A method of personalizing query suggestions, comprising: receiving a query via computer-enabled query application; determining a first score for each of one or more people, wherein the first score is based on a frequency with which a querying user has selected each of the one or more people from previous query suggestions produced by the query application; determining a second score for each of the one or more people based on interactions between the querying user and the one or more people in one or more applications other than the query application; combining the first score and the second score to form a combined score, wherein the second score contributes less than the first score to the combined score; ranking each of the one or more people based on the combined score; providing, based on the ranking, a people query suggestion in a query suggestion user interface; and providing an actor-action query suggestion in the query suggestion user interface for receiving information about a content item action associated with a person corresponding to the content item action. 4. The method of claim 1 , further comprising receiving a selection of the people query suggestion and automatically providing information about the corresponding person in a computer-enabled user interface. | 0.731169 |
8,903,894 | 29 | 30 | 29. An apparatus-implemented method carried out by a system comprising a processor and a memory, the method comprising: receiving, by a client proxy, of a first HTTP GET request generated by a web browser of a client apparatus for a first URL; recording, by the client proxy, of time of receipt of the first HTTP GET request; editing, by the client proxy, of Javascript to provide code configured to cause the web browser of the client apparatus to generate a second HTTP request; sending, by the client proxy, to the web browser of the client apparatus of an HTTP response comprising the code; generating by the web browser of the client apparatus of the second HTTP request in response to receipt of the HTTP response comprising the code; receiving, by the client proxy, of the second HTTP request; recording, by the client proxy, of time of receipt of the second HTTP request; and computing a response time in accordance with a difference between the time of receipt of the first HTTP GET request as recorded by the client proxy and the time of receipt of the second HTTP request as recorded by the client proxy. | 29. An apparatus-implemented method carried out by a system comprising a processor and a memory, the method comprising: receiving, by a client proxy, of a first HTTP GET request generated by a web browser of a client apparatus for a first URL; recording, by the client proxy, of time of receipt of the first HTTP GET request; editing, by the client proxy, of Javascript to provide code configured to cause the web browser of the client apparatus to generate a second HTTP request; sending, by the client proxy, to the web browser of the client apparatus of an HTTP response comprising the code; generating by the web browser of the client apparatus of the second HTTP request in response to receipt of the HTTP response comprising the code; receiving, by the client proxy, of the second HTTP request; recording, by the client proxy, of time of receipt of the second HTTP request; and computing a response time in accordance with a difference between the time of receipt of the first HTTP GET request as recorded by the client proxy and the time of receipt of the second HTTP request as recorded by the client proxy. 30. A method according to claim 29 , wherein the code is configured such that the second HTTP request is a last HTTP GET request carried out by the web browser when processing the HTTP response. | 0.580087 |
10,031,941 | 10 | 14 | 10. A method of evaluating search query terms in a computer network environment, comprising: obtaining, by a data processing system having one or more processors, from a computing device via a computer network, a first search query having a first plurality of search terms and a second search query having a second plurality of search terms; determining, by the data processing system, a relationship between the first search query and the second search query based on the first plurality of search terms and the second plurality of search terms; identifying, by the data processing system and based on the relationship between the first search query and the second search query, a search term from the first plurality of search terms and a supplemental term absent from the first search query and absent from the second search query; generating, by the data processing system, a structured search query comprising the second search query, the search term from the first plurality of search terms, and the supplemental term absent from the first search query and absent from the second search query; selecting, by the data processing system in response to the second search query and based on the structured search query comprising the second search query, the search term from the first plurality of search terms, and the supplemental term absent from the first search query and absent from the second search query, a content item comprising a uniform resource identifier comprising a representation of the structured search query, the content item configured to transmit the uniform resource identifier to a second computing device associated with the content item based on the content item receiving an indication of an input; and transmitting, to the computing device, the content item in response to the second search query. | 10. A method of evaluating search query terms in a computer network environment, comprising: obtaining, by a data processing system having one or more processors, from a computing device via a computer network, a first search query having a first plurality of search terms and a second search query having a second plurality of search terms; determining, by the data processing system, a relationship between the first search query and the second search query based on the first plurality of search terms and the second plurality of search terms; identifying, by the data processing system and based on the relationship between the first search query and the second search query, a search term from the first plurality of search terms and a supplemental term absent from the first search query and absent from the second search query; generating, by the data processing system, a structured search query comprising the second search query, the search term from the first plurality of search terms, and the supplemental term absent from the first search query and absent from the second search query; selecting, by the data processing system in response to the second search query and based on the structured search query comprising the second search query, the search term from the first plurality of search terms, and the supplemental term absent from the first search query and absent from the second search query, a content item comprising a uniform resource identifier comprising a representation of the structured search query, the content item configured to transmit the uniform resource identifier to a second computing device associated with the content item based on the content item receiving an indication of an input; and transmitting, to the computing device, the content item in response to the second search query. 14. The method of claim 10 , wherein the structured search query indicates at least one of a content identifier and a geographic location identifier. | 0.892651 |
9,558,467 | 15 | 20 | 15. A method of creating and/or updating a computerized model usable in connection with an enterprise modeling platform, the computerized model being defined in connection with a first modeling language, the method comprising: receiving an image of a hand-drawn model, the hand-drawn model existing on a physical substrate and following rules associated with a second modeling language, the first and second modeling languages being different from one another; performing, using processing resources including at least one processor and a memory operably coupled thereto, image processing on the image of the hand-drawn model, the image processing including a plurality of different identification levels, the different identification levels respectively corresponding to recognitions of (a) structures in the image that correspond to objects in the hand-drawn model, (b) object types for the identified structures that correspond to the objects, (c) text associated with the identified structures that correspond to the objects, and (d) connections between at least some of the identified structures that correspond to the objects; generating, using the processing resources, a digitized iteratively-reviewed version of the hand-drawn model by: presenting, on a display device and on an identification level by identification level basis, results of the recognitions corresponding to the respective identification levels, and accepting user modification(s) to the results on the identification level by identification level basis; and transforming the digitized iteratively-reviewed version of the hand-drawn model into the computerized model in accordance with a set of rules defining relationships between elements in the first and second modeling languages. | 15. A method of creating and/or updating a computerized model usable in connection with an enterprise modeling platform, the computerized model being defined in connection with a first modeling language, the method comprising: receiving an image of a hand-drawn model, the hand-drawn model existing on a physical substrate and following rules associated with a second modeling language, the first and second modeling languages being different from one another; performing, using processing resources including at least one processor and a memory operably coupled thereto, image processing on the image of the hand-drawn model, the image processing including a plurality of different identification levels, the different identification levels respectively corresponding to recognitions of (a) structures in the image that correspond to objects in the hand-drawn model, (b) object types for the identified structures that correspond to the objects, (c) text associated with the identified structures that correspond to the objects, and (d) connections between at least some of the identified structures that correspond to the objects; generating, using the processing resources, a digitized iteratively-reviewed version of the hand-drawn model by: presenting, on a display device and on an identification level by identification level basis, results of the recognitions corresponding to the respective identification levels, and accepting user modification(s) to the results on the identification level by identification level basis; and transforming the digitized iteratively-reviewed version of the hand-drawn model into the computerized model in accordance with a set of rules defining relationships between elements in the first and second modeling languages. 20. The method of claim 15 , further comprising generating and displaying in separate layers representations of the recognized objects and the image of the hand-drawn model. | 0.90226 |
9,311,607 | 13 | 14 | 13. The information processing device according to claim 1 , further comprising: search result acquisition code configured to cause the at least one processor to acquire a first search result using the base word as the search keyword and a second search result using the compound word as the search keyword; and search result information generation code configured to cause the at least one processor to generate search result information so that at least a portion of the first search result and the second search result acquired by the search result acquisition code are made to be distinguished and displayed on the screen of the display of the user terminal device. | 13. The information processing device according to claim 1 , further comprising: search result acquisition code configured to cause the at least one processor to acquire a first search result using the base word as the search keyword and a second search result using the compound word as the search keyword; and search result information generation code configured to cause the at least one processor to generate search result information so that at least a portion of the first search result and the second search result acquired by the search result acquisition code are made to be distinguished and displayed on the screen of the display of the user terminal device. 14. The information processing device according to claim 13 , wherein the search result information generation code causes the at least one processor to generate the search result information so that the search result obtained by removing a portion of the second search result from the first search result is made to be displayed as at least the portion of the first search result. | 0.94765 |
8,639,517 | 1 | 4 | 1. A method comprising: generating, via a processor, a set of features characterizing an association between a user input and a conversation context using prior user inputs; determining, by normalizing a length of the user input to a previous input in the prior user inputs and using a data-driven machine learning approach, whether the user input is associated with an existing topic related to a previous conversation context; and when the user input is associated with the existing topic, generating a response to the user input using information associated with the user input and content associated with any previous user input on the existing topic. | 1. A method comprising: generating, via a processor, a set of features characterizing an association between a user input and a conversation context using prior user inputs; determining, by normalizing a length of the user input to a previous input in the prior user inputs and using a data-driven machine learning approach, whether the user input is associated with an existing topic related to a previous conversation context; and when the user input is associated with the existing topic, generating a response to the user input using information associated with the user input and content associated with any previous user input on the existing topic. 4. The method of claim 1 , wherein the user input is a natural language request. | 0.903382 |
9,355,385 | 9 | 14 | 9. A server system comprising: one or more computing devices associated with an email and calendaring server, at least one of the computing devices providing an API server that: invokes a find places method in response to a request message comprising content from a location field within a meeting item from a client of the email and calendaring service, wherein the meeting item includes: a meeting request form, appointment, email, calendar entry, or a contact entry, the find places method defined by an API provided by the API server; and sends a response message to the client in reply to the request message, the response message comprising results of the find place method, the results comprising location information associated with a place name or source-related identifier indicated by the request message, wherein the find place method comprises: parsing the request message for the place name, street address, or the source-related identifier; querying a web service, mailbox, and/or managed database using the place name, the street address, or the source-related identifier; receiving results of the query; and filtering and formatting the results to generate the response message. | 9. A server system comprising: one or more computing devices associated with an email and calendaring server, at least one of the computing devices providing an API server that: invokes a find places method in response to a request message comprising content from a location field within a meeting item from a client of the email and calendaring service, wherein the meeting item includes: a meeting request form, appointment, email, calendar entry, or a contact entry, the find places method defined by an API provided by the API server; and sends a response message to the client in reply to the request message, the response message comprising results of the find place method, the results comprising location information associated with a place name or source-related identifier indicated by the request message, wherein the find place method comprises: parsing the request message for the place name, street address, or the source-related identifier; querying a web service, mailbox, and/or managed database using the place name, the street address, or the source-related identifier; receiving results of the query; and filtering and formatting the results to generate the response message. 14. The server system of claim 9 , wherein the request message comprises at least one parameter selected from the group consisting of a query string, a source-related location identifier, a culture parameter, a maximum number of results, a source of location information, and geo-coordinates of a location or user. | 0.580214 |
9,747,640 | 11 | 12 | 11. A non-transitory computer readable medium comprising instructions encoded thereon for calculating a trust score, the instructions comprising: instructions for retrieving, from a first database using processing circuitry, first data associated with a first entity in a computer network; instructions for calculating a first component score based on the first data; instructions for retrieving, from a second database using the processing circuitry, second data associated with the first entity; instructions for calculating a second component score based on the second data; instructions for calculating a weighted combination of the first component score and the second component score to produce a trust score for the first entity; instructions for receiving, from a user device of a second entity in the computer network, data indicating an attribute associated with the first entity; instructions for recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity; instructions for updating the trust score for the first entity by calculating a weighted combination of the recalculated first component score and the second component score; wherein the instructions for receiving, from the user device of the second entity, the data indicating an attribute associated with the first entity comprise instructions for receiving an indication of a user input from the second entity that validates the first data; and wherein the instructions for recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity comprise instructions for improving the first component score by a predetermined amount until a threshold component score is reached. | 11. A non-transitory computer readable medium comprising instructions encoded thereon for calculating a trust score, the instructions comprising: instructions for retrieving, from a first database using processing circuitry, first data associated with a first entity in a computer network; instructions for calculating a first component score based on the first data; instructions for retrieving, from a second database using the processing circuitry, second data associated with the first entity; instructions for calculating a second component score based on the second data; instructions for calculating a weighted combination of the first component score and the second component score to produce a trust score for the first entity; instructions for receiving, from a user device of a second entity in the computer network, data indicating an attribute associated with the first entity; instructions for recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity; instructions for updating the trust score for the first entity by calculating a weighted combination of the recalculated first component score and the second component score; wherein the instructions for receiving, from the user device of the second entity, the data indicating an attribute associated with the first entity comprise instructions for receiving an indication of a user input from the second entity that validates the first data; and wherein the instructions for recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity comprise instructions for improving the first component score by a predetermined amount until a threshold component score is reached. 12. The non-transitory computer readable medium of claim 11 , the instructions further comprising: instructions for receiving a request for the trust score for the first entity from a user device of a third entity in the computer network; instructions for retrieving, using the processing circuitry, data indicating paths in the computer network; and instructions for identifying, based on the retrieved data indicating paths in the computer network, a path connecting the third entity to the second entity in the computer network, the path comprising a number of links that is less than a threshold number of links; wherein the instructions for recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity comprise instructions for improving the first component score by a predetermined amount. | 0.500569 |
9,477,929 | 1 | 11 | 1. A computer method, comprising carrying out operations on a computer, the operations comprising: maintaining machine readable embodiments on a medium of a bipartite graph and a tripartite graph, the tripartite graph comprising a first plurality of nodes corresponding to labeled and unlabeled examples from source and target domains; a second plurality of nodes corresponding to features; and a first plurality of edges connecting the nodes corresponding to the features to the nodes corresponding to the examples according to whether the features appear in the examples or not; the bipartite graph comprising the first plurality of nodes corresponding to the examples; and a second plurality of edges connecting the examples, the edges being associated with indications that indicate whether connected examples are in a same domain or not; deriving labels for at least one target domain based on the tripartite and bipartite graphs; and presenting an embodiment of the labels as a result, wherein said deriving comprises: formulating an objective function based on said bipartite and tripartite graphs, said objective function encompassing smoothness and consistency constraints and providing label information in the target domain at least responsive to label information in the source domain; applying the objective function to the all examples, whether labeled or unlabeled, and all features in order to obtain at least one result relative to the unlabeled examples; minimizing the objective function to yield a label function; and providing output labels responsive to the label function. | 1. A computer method, comprising carrying out operations on a computer, the operations comprising: maintaining machine readable embodiments on a medium of a bipartite graph and a tripartite graph, the tripartite graph comprising a first plurality of nodes corresponding to labeled and unlabeled examples from source and target domains; a second plurality of nodes corresponding to features; and a first plurality of edges connecting the nodes corresponding to the features to the nodes corresponding to the examples according to whether the features appear in the examples or not; the bipartite graph comprising the first plurality of nodes corresponding to the examples; and a second plurality of edges connecting the examples, the edges being associated with indications that indicate whether connected examples are in a same domain or not; deriving labels for at least one target domain based on the tripartite and bipartite graphs; and presenting an embodiment of the labels as a result, wherein said deriving comprises: formulating an objective function based on said bipartite and tripartite graphs, said objective function encompassing smoothness and consistency constraints and providing label information in the target domain at least responsive to label information in the source domain; applying the objective function to the all examples, whether labeled or unlabeled, and all features in order to obtain at least one result relative to the unlabeled examples; minimizing the objective function to yield a label function; and providing output labels responsive to the label function. 11. The method of claim 1 , wherein the objective function is a weighted combination of label smoothness on the tripartite graph, label smoothness on the bipartite graph, and consistency with the label information and the prior knowledge. | 0.860165 |
9,047,379 | 1 | 12 | 1. A computer implemented method comprising: receiving by a search engine, operating on a computing device, from a content searching or consuming application, an atomic search term, the search engine and the content searching or consuming application being operated on one or more different or same computing devices; receiving content nominally associated with the atomic search term, or access information of the content, by the search engine; generating, by the search engine, one or more scores for one or more structures of the content indicative of relative relevance of the content or one or more portions of the content to the atomic search term, wherein the generating of a score for a structure is based at least in part on a distance function and a scoring function, wherein the structure has sub-structures structurally describing at least a portion of the content, and having content nodes and/or text strings, wherein the sub-structures are hierarchically organized with the one or more portions of the content in a sub-structure at a level respectively assigned one or more positions according to a geometry established for that level, wherein the distance function measures distances between sub-structures within the structure, and the scoring function is positionally sensitive, yielding different scores for different occurrence positions of the atomic search term in the sub-structures; and conditionally providing or not providing the content or one or more portions of the content, or access information of the content or one or more portions of the content, to the content searching or consuming application, by the search engine, based at least in part on the generated one or more scores; wherein the generating of a score for a structure further includes at each level, linearly iterating over one or more portions of the content at the level to capture potential of a portion to influence other portions of the level, and influence received by a portion from the other portions of the level. | 1. A computer implemented method comprising: receiving by a search engine, operating on a computing device, from a content searching or consuming application, an atomic search term, the search engine and the content searching or consuming application being operated on one or more different or same computing devices; receiving content nominally associated with the atomic search term, or access information of the content, by the search engine; generating, by the search engine, one or more scores for one or more structures of the content indicative of relative relevance of the content or one or more portions of the content to the atomic search term, wherein the generating of a score for a structure is based at least in part on a distance function and a scoring function, wherein the structure has sub-structures structurally describing at least a portion of the content, and having content nodes and/or text strings, wherein the sub-structures are hierarchically organized with the one or more portions of the content in a sub-structure at a level respectively assigned one or more positions according to a geometry established for that level, wherein the distance function measures distances between sub-structures within the structure, and the scoring function is positionally sensitive, yielding different scores for different occurrence positions of the atomic search term in the sub-structures; and conditionally providing or not providing the content or one or more portions of the content, or access information of the content or one or more portions of the content, to the content searching or consuming application, by the search engine, based at least in part on the generated one or more scores; wherein the generating of a score for a structure further includes at each level, linearly iterating over one or more portions of the content at the level to capture potential of a portion to influence other portions of the level, and influence received by a portion from the other portions of the level. 12. At least one non-transitory computer-readable storage medium comprising programming instructions configured, in response to execution of the programming instruction by a computing apparatus, to cause the computing apparatus to perform the computer implemented method of claim 1 . | 0.857789 |
8,862,252 | 33 | 34 | 33. The electronic device of claim 20 , wherein the first menu audio clip that is played back is associated with a first menu option of the menu. | 33. The electronic device of claim 20 , wherein the first menu audio clip that is played back is associated with a first menu option of the menu. 34. The electronic device of claim 33 , wherein the processor is further operative to, while the audio output is playing back the first menu audio clip: receive from the single sensing element a second user input that is detected by the single sensing element; and in response to the receiving the second user input, access the first menu option. | 0.858313 |
8,032,519 | 15 | 16 | 15. The method of claim 13 , further comprising filtering the snippets using one or more pre-ranking filters and one or more post-ranking filters. | 15. The method of claim 13 , further comprising filtering the snippets using one or more pre-ranking filters and one or more post-ranking filters. 16. The method of claim 15 , further comprising filtering the snippets using the one or more pre-ranking filters and one or more post-ranking filters selected from a query filter, a punctuation filter, a title filter, and a similarity filter. | 0.894231 |
9,753,911 | 23 | 38 | 23. A computerized method comprising: receiving two or more, user selected, currently displayed objects in an editable visual page to be edited in a website building system, wherein at least one of said selected objects of said selection has pre-defined customizable attributes and non-customizable attributes, wherein each said customizable attribute has at least one customization record including at least a customization ID; sorting said customizable attributes of said at least two selected objects according to said customization IDs; and building a customization user interface specific to said selected objects by uniting said customization records according to common customization IDs into a set of lists, each list having attributes with customization records sharing a common customization ID and to generate dialog elements according to said lists and; displaying said user interface based on said customizable attributes of said selected objects. | 23. A computerized method comprising: receiving two or more, user selected, currently displayed objects in an editable visual page to be edited in a website building system, wherein at least one of said selected objects of said selection has pre-defined customizable attributes and non-customizable attributes, wherein each said customizable attribute has at least one customization record including at least a customization ID; sorting said customizable attributes of said at least two selected objects according to said customization IDs; and building a customization user interface specific to said selected objects by uniting said customization records according to common customization IDs into a set of lists, each list having attributes with customization records sharing a common customization ID and to generate dialog elements according to said lists and; displaying said user interface based on said customizable attributes of said selected objects. 38. The method according to claim 23 and wherein said user interface is at least one of linear, hierarchical and two-dimensional. | 0.835878 |
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