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4. The method of claim 1 wherein forming a fingerprint of the e-mail by linking together the extracted HTML tags comprises: concatenating the extracted HTML tags to form the single string. | 4. The method of claim 1 wherein forming a fingerprint of the e-mail by linking together the extracted HTML tags comprises: concatenating the extracted HTML tags to form the single string. 5. The method of claim 4 wherein the concatenated extracted HTML tags include separation codes demarcating where the extracted HTML tags have been concatenated together. | 0.765487 |
8. A memory device storing computer program instructions that, when executed by a processor of a computer, cause the computer to perform a computer-implemented method comprising: receiving a query including: a selected record, an outer join that provides a joined table having NULLab 1 e records, and an Order By clause that provides a sort order for ordering records in the joined table based on one or more fields of the joined table; and generating, by the server, a separate query configured to fetch from the joined table a current row that corresponds to the selected record and either subsequent rows or previous rows relative to the current row, wherein generating the separate query comprises: determining whether a paging direction of the separate query is forward paging or backward paging, determining whether the sort order for the Order By clause is ascending or descending, determining an original inequality operator based on the sort order for the Order By clause and the paging direction of the separate query, determining whether the current row returns a NULL value, and generating a WHERE condition for the separate query configured to either change the original inequality operator or ignore the original inequality operator depending on whether the paging direction of the separate query is forward paging or backward paging, whether the sort order for the Order By clause is ascending or descending, and whether the current row returns a NULL value. | 8. A memory device storing computer program instructions that, when executed by a processor of a computer, cause the computer to perform a computer-implemented method comprising: receiving a query including: a selected record, an outer join that provides a joined table having NULLab 1 e records, and an Order By clause that provides a sort order for ordering records in the joined table based on one or more fields of the joined table; and generating, by the server, a separate query configured to fetch from the joined table a current row that corresponds to the selected record and either subsequent rows or previous rows relative to the current row, wherein generating the separate query comprises: determining whether a paging direction of the separate query is forward paging or backward paging, determining whether the sort order for the Order By clause is ascending or descending, determining an original inequality operator based on the sort order for the Order By clause and the paging direction of the separate query, determining whether the current row returns a NULL value, and generating a WHERE condition for the separate query configured to either change the original inequality operator or ignore the original inequality operator depending on whether the paging direction of the separate query is forward paging or backward paging, whether the sort order for the Order By clause is ascending or descending, and whether the current row returns a NULL value. 13. The memory device of claim 8 , wherein: the original inequality operator is changed to include an OR FIELD IS NULL condition when the paging direction of the separate query is backward paging, the sort order for the Order By clause is ascending, and the current row returns only non-NULL values. | 0.655574 |
13. A method of automatically sorting disaster and/or accident related news stories by their temporal characteristics using a computing system comprising: a) identifying a first news vent involving a disaster and/or accident related event; wherein said first news event is associated by the computing system with a plurality of corresponding event status states defined for a progress template for such first news event; wherein said event status states are associated by the computing system with content for the first news event which is distinctive to different temporal periods within said progress template; b) analyzing a first electronic document describing said first event with the computing system to identify first content snippets determinative of a first status state of said first news event relative to said event status states defined for said progress template; c) analyzing a second electronic document with second content snippets describing a second status state for said first news event with the computing system; and d) determining which of said first and second electronic documents contains content describing a more current status state of said first event by comparing said first status state to said second status state and generating an output with the computing system indicating which of said electronic documents describes the more current status state; wherein changes in corresponding content snippets relating to one of least property damage, loss of lives, injuries survivors and/or an absolute time of such first event are tracked between documents and used by the computing system to derive a relative temporal relationship between said first electronic document and second electronic document. | 13. A method of automatically sorting disaster and/or accident related news stories by their temporal characteristics using a computing system comprising: a) identifying a first news vent involving a disaster and/or accident related event; wherein said first news event is associated by the computing system with a plurality of corresponding event status states defined for a progress template for such first news event; wherein said event status states are associated by the computing system with content for the first news event which is distinctive to different temporal periods within said progress template; b) analyzing a first electronic document describing said first event with the computing system to identify first content snippets determinative of a first status state of said first news event relative to said event status states defined for said progress template; c) analyzing a second electronic document with second content snippets describing a second status state for said first news event with the computing system; and d) determining which of said first and second electronic documents contains content describing a more current status state of said first event by comparing said first status state to said second status state and generating an output with the computing system indicating which of said electronic documents describes the more current status state; wherein changes in corresponding content snippets relating to one of least property damage, loss of lives, injuries survivors and/or an absolute time of such first event are tracked between documents and used by the computing system to derive a relative temporal relationship between said first electronic document and second electronic document. 19. The method of claim 13 further including a step: predicting a subsequent location for said first news event with the computing system based on determining a current location. | 0.570465 |
1. A method comprising: receiving an arbitrary natural language communication from a user; applying a concept recognition process to automatically derive a representation of concepts embodied in the communication; using the concept representation to provide to a human agent information useful in responding to the natural language communication, wherein the information provided to the human agent includes a plurality of possible responses to the user's communication; enabling the human agent to select a response from the plurality of possible responses; and delivering the selected response to the user. | 1. A method comprising: receiving an arbitrary natural language communication from a user; applying a concept recognition process to automatically derive a representation of concepts embodied in the communication; using the concept representation to provide to a human agent information useful in responding to the natural language communication, wherein the information provided to the human agent includes a plurality of possible responses to the user's communication; enabling the human agent to select a response from the plurality of possible responses; and delivering the selected response to the user. 46. The method of claim 1 , wherein the selected response is delivered to the user at a later time relative to the communication. | 0.705882 |
11. A method, comprising: receiving, for at least one website, a first plurality of data points related to each visitor of a first plurality of visitors to the website, the first plurality of data points comprising at least an identification of the visitor and an interaction of the visitor with the website; performing, using a computing device, a clustering algorithm that generates a plurality of clusters using the first plurality of data points as input, each cluster of the plurality of clusters defined by a number of unique visitors and at least some of the unique visitors sharing at least one interaction in common; generating, for each cluster of the plurality of clusters, at least one assignment rule that associates a behavior common to at least some of the unique visitors in the cluster with the cluster; providing the at least one assignment rule to an updating process that assigns each visitor of a second plurality of visitors to the plurality of clusters using the at least one assignment rule; and providing the plurality of clusters to a targeting process that generates a similarity audience formed of at least some of the clusters and provides, via electronic transmission, at least some members of the similarity audience with digital content. | 11. A method, comprising: receiving, for at least one website, a first plurality of data points related to each visitor of a first plurality of visitors to the website, the first plurality of data points comprising at least an identification of the visitor and an interaction of the visitor with the website; performing, using a computing device, a clustering algorithm that generates a plurality of clusters using the first plurality of data points as input, each cluster of the plurality of clusters defined by a number of unique visitors and at least some of the unique visitors sharing at least one interaction in common; generating, for each cluster of the plurality of clusters, at least one assignment rule that associates a behavior common to at least some of the unique visitors in the cluster with the cluster; providing the at least one assignment rule to an updating process that assigns each visitor of a second plurality of visitors to the plurality of clusters using the at least one assignment rule; and providing the plurality of clusters to a targeting process that generates a similarity audience formed of at least some of the clusters and provides, via electronic transmission, at least some members of the similarity audience with digital content. 13. The method of claim 11 , further comprising: receiving, for at least one website, a second plurality of data points related to each visitor of a third plurality of visitors to the website, the second plurality of data points comprising at least an identification of the visitor and an interaction of the visitor with the website; assigning each visitor of the third plurality of visitors to at least one cluster of the plurality of clusters using the at least one assignment rule; re-assigning at least some visitors of the first plurality of visitors to at least one cluster of the plurality of clusters using the at least one assignment rule; determining whether to replace the plurality of clusters; and upon a determination to replace the plurality of clusters: performing the clustering algorithm a second time using the second plurality of data points and the first plurality of data points associated with the at least some visitors of the first plurality of visitors as input; and providing, to the targeting process, the plurality of clusters generated by performing the clustering algorithm the second time; otherwise: providing, to the targeting process, the plurality of clusters after the assigning and the re-assigning. | 0.5 |
1. A speech end-pointer system, comprising: a computer processor; a voice triggering module configured to identify a portion of an audio stream comprising a speech segment; and a rule module in communication with the voice triggering module, the rule module comprising a plurality of rules used by the computer processor to analyze the audio stream and detect a beginning and an end of the speech segment, where the plurality of rules comprises one or more rules based on an energy counter; where the beginning of the speech segment and the end of the speech segment represent boundaries between speech and non-speech portions of the audio stream; and where the computer processor is configured to determine whether a frame of the audio stream has energy above a background noise level and increment the energy counter by a length of the frame in response to a determination that the frame has energy above the background noise level. | 1. A speech end-pointer system, comprising: a computer processor; a voice triggering module configured to identify a portion of an audio stream comprising a speech segment; and a rule module in communication with the voice triggering module, the rule module comprising a plurality of rules used by the computer processor to analyze the audio stream and detect a beginning and an end of the speech segment, where the plurality of rules comprises one or more rules based on an energy counter; where the beginning of the speech segment and the end of the speech segment represent boundaries between speech and non-speech portions of the audio stream; and where the computer processor is configured to determine whether a frame of the audio stream has energy above a background noise level and increment the energy counter by a length of the frame in response to a determination that the frame has energy above the background noise level. 5. The system of claim 1 , where the plurality of rules includes a first rule configured to set the beginning of the speech segment or the end of the speech segment based on a comparison between the energy counter and a first threshold, and a second rule configured to set the beginning of the speech segment or the end of the speech segment based on a comparison between a lack of energy counter and a second threshold. | 0.573693 |
1. A method for using a computer system to provide additional material related to a concept within electronic text, comprising the steps of: a) identifying electronic text for display; b) packaging with said text computer-executable code, wherein: i. said code is formatted and designed to be executed in real-time without user action when said accompanying text is displayed; ii. when executed, said code submits a search request for additional information related to a concept represented within at least one text section of said identified text, said search request leading to a search of an index, said search of an index identifying additional material related to said concept; and iii. when executed, said code provides for display in the same presentation as said identified electronic text an indicator of said identified additional material, wherein said indicator comprises display material not derived from said electronic text; and c) in response to a request for said electronic text, providing said electronic text together with said computer-executable code; wherein said index contains a plurality of terms by which it may be searched; at least one term in said index is associated with at least one reference to a text section; and at least one term in said index is associated with a plurality of references, at least two of said plurality of references indicating different text sections. | 1. A method for using a computer system to provide additional material related to a concept within electronic text, comprising the steps of: a) identifying electronic text for display; b) packaging with said text computer-executable code, wherein: i. said code is formatted and designed to be executed in real-time without user action when said accompanying text is displayed; ii. when executed, said code submits a search request for additional information related to a concept represented within at least one text section of said identified text, said search request leading to a search of an index, said search of an index identifying additional material related to said concept; and iii. when executed, said code provides for display in the same presentation as said identified electronic text an indicator of said identified additional material, wherein said indicator comprises display material not derived from said electronic text; and c) in response to a request for said electronic text, providing said electronic text together with said computer-executable code; wherein said index contains a plurality of terms by which it may be searched; at least one term in said index is associated with at least one reference to a text section; and at least one term in said index is associated with a plurality of references, at least two of said plurality of references indicating different text sections. 2. The method of claim 1 , wherein said electronic text comprises non-text elements. | 0.734375 |
1. A computer-implemented method for estimating confidence scores of unverified signatures, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: detecting a potentially malicious event that triggers a malware signature designed to detect malware, the malware signature having a confidence score that: represents a level of confidence in the accuracy or reliability of the malware signature; and is above a certain threshold such that the malware signature's confidence score indicates a threshold level of confidence in the accuracy or reliability of the malware signature; detecting another event that triggers another signature designed to detect malware, the other signature having a confidence score that: represents a level of confidence in the accuracy or reliability of the other signature; and is unknown such that the other signature's confidence score indicates an unknown level of confidence in the accuracy or reliability of the other signature; determining that the potentially malicious event and the other event occurred within a certain time period of one another; and assigning, to the other signature, a confidence score based at least in part on the potentially malicious event and the other event occurring within the certain time period of one another. | 1. A computer-implemented method for estimating confidence scores of unverified signatures, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: detecting a potentially malicious event that triggers a malware signature designed to detect malware, the malware signature having a confidence score that: represents a level of confidence in the accuracy or reliability of the malware signature; and is above a certain threshold such that the malware signature's confidence score indicates a threshold level of confidence in the accuracy or reliability of the malware signature; detecting another event that triggers another signature designed to detect malware, the other signature having a confidence score that: represents a level of confidence in the accuracy or reliability of the other signature; and is unknown such that the other signature's confidence score indicates an unknown level of confidence in the accuracy or reliability of the other signature; determining that the potentially malicious event and the other event occurred within a certain time period of one another; and assigning, to the other signature, a confidence score based at least in part on the potentially malicious event and the other event occurring within the certain time period of one another. 10. The method of claim 1 , wherein assigning the confidence score to the other signature comprises: updating a signature database that facilitates distribution of signatures to computing devices within a user base to account for the confidence score assigned to the other signature; and enabling, based at least in part on updating the signature database, the computing devices within the user base to leverage the confidence score assigned to the other signature in assessing suspicious events detected on the computing devices. | 0.625435 |
3. The method of claim 1 , wherein the background model comprises a finite state automaton. | 3. The method of claim 1 , wherein the background model comprises a finite state automaton. 4. The method of claim 3 wherein, in the finite state automaton, transitions between states are associated with respective probabilities, and wherein transitions between the target background model and subsequences of the semantic representation are associated with a respective probability which is lower than a probability assigned to a transition between two characters in the semantic representation. | 0.908749 |
5. In an automated data extraction environment, a non-transitory computer readable storage medium having instructions that when executed by a processor responsive to the instructions, perform a method of generating a confidence attribute comprising: scanning a set of data items, each data item corresponding to a control data value; generating, in a series of transformations, a recognized value from the scanned data item, the series of transformations defining a combined sequence from an input stream of data form to a final data value to convert the scanned data item to the recognized value, each of the transformations in the series converting the data item to a different form of the recognized value; determining, for each of the transformations, a component confidence, the component confidence indicative of a likelihood of accurate conversion from an input form to the different form; combining each of the component confidences determined for a particular data item in a weighted manner using a non-linear statistical model to generate a final confidence; and comparing, in a learning mode, the recognized value from a final transformation of the data item to the corresponding control data value, the recognized value defining a business relevant data value, the final confidence being indicative of the data value being a true representation of the original value in the input data stream. | 5. In an automated data extraction environment, a non-transitory computer readable storage medium having instructions that when executed by a processor responsive to the instructions, perform a method of generating a confidence attribute comprising: scanning a set of data items, each data item corresponding to a control data value; generating, in a series of transformations, a recognized value from the scanned data item, the series of transformations defining a combined sequence from an input stream of data form to a final data value to convert the scanned data item to the recognized value, each of the transformations in the series converting the data item to a different form of the recognized value; determining, for each of the transformations, a component confidence, the component confidence indicative of a likelihood of accurate conversion from an input form to the different form; combining each of the component confidences determined for a particular data item in a weighted manner using a non-linear statistical model to generate a final confidence; and comparing, in a learning mode, the recognized value from a final transformation of the data item to the corresponding control data value, the recognized value defining a business relevant data value, the final confidence being indicative of the data value being a true representation of the original value in the input data stream. 7. The method of claim 5 further comprising: computing, the final confidence for each business relevant data value from the combined component confidence values derived from the transformations; using, in the learning mode, the component confidence for calculation of the final confidence only if the component confidence is found to be statistically significant and favorably impacting the determination of the final confidence; combining the component confidence with an associated weight determined during the learning mode; and computing the final confidence based on a non-linear statistical model including the associated weight, a the model being generated during the learning phase. | 0.650077 |
16. The non-transitory storage device of claim 15 , where generating the metadata from the unstructured data includes: extracting the metadata from the document; and incorporating user created document attributes into the extracted metadata. | 16. The non-transitory storage device of claim 15 , where generating the metadata from the unstructured data includes: extracting the metadata from the document; and incorporating user created document attributes into the extracted metadata. 18. The non-transitory storage device of claim 16 , the operations further comprising: receiving the document from a client device; and storing the received document in a document repository. | 0.88902 |
1. A method of searching in an overlay network, comprising: receiving a query at a first node in a distributed network from a querying node, wherein the query includes a first keyword and a second keyword; finding a first set of a first number of documents that contain the first keyword; computing an optimal first Bloom filter length and a corresponding first number of hash functions as a function of the first number of documents in the first set; determining a second node responsible for finding a set of documents that contain the second keyword based on a hashed second keyword; generating a Bloom filter of the first set comprising an array having the first Bloom filter length and the first number of hash functions; sending the first Bloom filter of the first set to the second node in the distributed network to generate a result for the searching; returning, by the first node, documents consisting of the first set of documents to the querying node; finding, at the second node, a second set of a second number of documents that contain the second keyword; checking, at the second node, a membership of each of the documents in the second set over the first Bloom filter to determine a third set of documents that contain the second keyword and are not already present in the first Bloom filter; and returning, by second node, documents consisting of the third set of documents to the querying node. | 1. A method of searching in an overlay network, comprising: receiving a query at a first node in a distributed network from a querying node, wherein the query includes a first keyword and a second keyword; finding a first set of a first number of documents that contain the first keyword; computing an optimal first Bloom filter length and a corresponding first number of hash functions as a function of the first number of documents in the first set; determining a second node responsible for finding a set of documents that contain the second keyword based on a hashed second keyword; generating a Bloom filter of the first set comprising an array having the first Bloom filter length and the first number of hash functions; sending the first Bloom filter of the first set to the second node in the distributed network to generate a result for the searching; returning, by the first node, documents consisting of the first set of documents to the querying node; finding, at the second node, a second set of a second number of documents that contain the second keyword; checking, at the second node, a membership of each of the documents in the second set over the first Bloom filter to determine a third set of documents that contain the second keyword and are not already present in the first Bloom filter; and returning, by second node, documents consisting of the third set of documents to the querying node. 5. The method of claim 1 , wherein computing the first Bloom filter length, L s , for the first set, D1, further comprises computing according to the following equation: L s = D 1 ( ln 2 ) 2 × ln ( 1 2 · 1 1 - R des ) and wherein computing first number of hash functions, r s , for the first set, D1, further comprises computing according to the following equation: r s = log 2 ( 1 2 · 1 1 - R des ) wherein R des is a desired recall rate of the Bloom filter. | 0.629472 |
23. A system comprising: a processor; and a memory storing instructions that, when executed, cause the system to: detect a provisioning trigger event; determine a state of a journey associated with a user based on the provisioning trigger event; determine one or more interest places based on the state of the journey; populate a place vocabulary associated with the user using the one or more interest places; filter the place vocabulary based on one or more place filtering parameters including a first location associated with the user, to filter the place vocabulary including determining a size of the place vocabulary, configuring a size of a coverage range associated with the first location based on the size of the place vocabulary, and generating the filtered place vocabulary that includes one or more custom place terms corresponding to one or more second locations within the coverage range; register the filtered place vocabulary for the user; receive a speech command from the user; recognize the one or more custom place terms in the speech command based on the registered place vocabulary; send data describing the speech command that includes the one or more custom place terms; and receive a result that matches the speech command including the one or more custom place terms. | 23. A system comprising: a processor; and a memory storing instructions that, when executed, cause the system to: detect a provisioning trigger event; determine a state of a journey associated with a user based on the provisioning trigger event; determine one or more interest places based on the state of the journey; populate a place vocabulary associated with the user using the one or more interest places; filter the place vocabulary based on one or more place filtering parameters including a first location associated with the user, to filter the place vocabulary including determining a size of the place vocabulary, configuring a size of a coverage range associated with the first location based on the size of the place vocabulary, and generating the filtered place vocabulary that includes one or more custom place terms corresponding to one or more second locations within the coverage range; register the filtered place vocabulary for the user; receive a speech command from the user; recognize the one or more custom place terms in the speech command based on the registered place vocabulary; send data describing the speech command that includes the one or more custom place terms; and receive a result that matches the speech command including the one or more custom place terms. 28. The system of claim 23 , wherein the instructions when executed cause the system to also: receive contacts data associated with the user; and determine the one or more interest places further based on location data in the contacts data. | 0.623453 |
24. The method of claim 23 , where initiating execution of the event detection engine comprises: initiating execution of a tokenizer on the event description to generate a tokenized description; and tagging tokens in the tokenized description to provide a tagged description. | 24. The method of claim 23 , where initiating execution of the event detection engine comprises: initiating execution of a tokenizer on the event description to generate a tokenized description; and tagging tokens in the tokenized description to provide a tagged description. 25. The method of claim 24 , further comprising: performing named entity recognition on the tagged description; and performing template matching to determine event attribute values for the event type. | 0.930252 |
23. A computer-implemented method, comprising: during an image capture mode, receiving, at a mobile computing device having one or more processors, an image capture request; in response to the image capture request: capturing, at the mobile computing device, an image of an object comprising a text in a source language; obtaining, at the mobile computing device, the text; and determining, at the mobile computing device, the source language of the text; in response to the image capture request and determining the source language of the text, determining, at the mobile computing device, whether to translate the text to a different target language; and in response to determining to translate the text to the target language: determining, at the mobile computing device, a degree of translation complexity for performing machine language translation of the text from the source language to the target language; transmitting, from the mobile computing device to a server, at least a portion of the text based on the degree of translation complexity; receiving, at the mobile computing device from the server, machine language translation results; obtaining, at the mobile computing device, a translated text based on the machine language translation results; obtaining, at the mobile computing device, a modified image by modifying (i) the image to replace the text with the translated text and (ii) a styling of the translated text such that its styling differs from a styling of the text; and outputting, at a display of the mobile computing device, the modified image. | 23. A computer-implemented method, comprising: during an image capture mode, receiving, at a mobile computing device having one or more processors, an image capture request; in response to the image capture request: capturing, at the mobile computing device, an image of an object comprising a text in a source language; obtaining, at the mobile computing device, the text; and determining, at the mobile computing device, the source language of the text; in response to the image capture request and determining the source language of the text, determining, at the mobile computing device, whether to translate the text to a different target language; and in response to determining to translate the text to the target language: determining, at the mobile computing device, a degree of translation complexity for performing machine language translation of the text from the source language to the target language; transmitting, from the mobile computing device to a server, at least a portion of the text based on the degree of translation complexity; receiving, at the mobile computing device from the server, machine language translation results; obtaining, at the mobile computing device, a translated text based on the machine language translation results; obtaining, at the mobile computing device, a modified image by modifying (i) the image to replace the text with the translated text and (ii) a styling of the translated text such that its styling differs from a styling of the text; and outputting, at a display of the mobile computing device, the modified image. 24. The computer-implemented method of claim 23 , further comprising: performing, at the mobile computing device, machine language translation for the entire text when the degree of translation complexity is less than a first translation complexity threshold, wherein the first translation complexity threshold represents a degree of translation complexity that the mobile computing device is appropriate for performing itself; and transmitting, from the mobile computing device to the server, at least the portion of the text when the degree of translation complexity is greater than the first translation complexity threshold. | 0.586112 |
2. The method of claim 1 , further comprising: modifying, by the system, the speech synthesis voice associated with the user based at least in part on the modification. | 2. The method of claim 1 , further comprising: modifying, by the system, the speech synthesis voice associated with the user based at least in part on the modification. 3. The method of claim 2 , wherein the speech synthesis voice comprises a series of parameters, wherein each parameter from the series of parameters comprises a value, wherein modifying the speech synthesis voice comprises: converting, by the system, the portion of the respective word into a phonetic representation of the portion of the respective word; converting, by the system, the corresponding portion of the voicemail into an audio sample of the corresponding portion of the voicemail; deriving, by the system, a relationship between the phonetic representation of the respective word and the audio sample of the corresponding portion of the voicemail; and modifying, by the system, the values of each parameter of the speech synthesis voice based on the relationship. | 0.831745 |
1. A method of enabling input into a handheld electronic device having an input apparatus, an output apparatus, and a memory having stored therein a plurality of language objects and a plurality of frequency objects, at least some of the language objects each being associated with an associated frequency object, at least some of the language objects each comprising a number of linguistic elements, the input apparatus including a plurality of input members, each of at least some of the input members having a plurality of the linguistic elements assigned thereto, the method comprising: detecting an ambiguous input; generating a number of compound language solutions by, for each compound language solution, identifying a language object corresponding with an initial portion of the ambiguous input and having a length equal to the length of the initial portion, and identifying another language object corresponding with another portion of the ambiguous input; for at least a first compound language solution, generating a junction object comprising a terminal linguistic element of the language object and an initial linguistic element of the another language object, and making a determination that at least one of: the junction object corresponds with a language object associated with a frequency object having a frequency value below a predetermined threshold, and no language object corresponds with the junction object; outputting with the output apparatus a representation of each of at least some of the compound language solutions, each said representation comprising a representation of the language object and a representation of at least a portion of the another language object; and at least one of: outputting a representation of the at least first compound language solution at a position of relatively lower priority than a representation of another compound language solution, and suppressing from the output the at least first compound language solution. | 1. A method of enabling input into a handheld electronic device having an input apparatus, an output apparatus, and a memory having stored therein a plurality of language objects and a plurality of frequency objects, at least some of the language objects each being associated with an associated frequency object, at least some of the language objects each comprising a number of linguistic elements, the input apparatus including a plurality of input members, each of at least some of the input members having a plurality of the linguistic elements assigned thereto, the method comprising: detecting an ambiguous input; generating a number of compound language solutions by, for each compound language solution, identifying a language object corresponding with an initial portion of the ambiguous input and having a length equal to the length of the initial portion, and identifying another language object corresponding with another portion of the ambiguous input; for at least a first compound language solution, generating a junction object comprising a terminal linguistic element of the language object and an initial linguistic element of the another language object, and making a determination that at least one of: the junction object corresponds with a language object associated with a frequency object having a frequency value below a predetermined threshold, and no language object corresponds with the junction object; outputting with the output apparatus a representation of each of at least some of the compound language solutions, each said representation comprising a representation of the language object and a representation of at least a portion of the another language object; and at least one of: outputting a representation of the at least first compound language solution at a position of relatively lower priority than a representation of another compound language solution, and suppressing from the output the at least first compound language solution. 2. The method of claim 1 wherein said language objects comprise a number of word objects and a number of n-gram objects, further comprising making as said determination a determination that at least one of: the junction object corresponds with an n-gram object associated with a frequency object having a frequency value below a predetermined threshold, and no n-gram object corresponds with the junction object. | 0.732859 |
20. The system of claim 14 wherein the visual representation enables the user to input the input parameter by selecting the visual representation via a touch screen. | 20. The system of claim 14 wherein the visual representation enables the user to input the input parameter by selecting the visual representation via a touch screen. 21. The system of claim 20 wherein the visual representation includes fill in the blank field entries requiring additional user input. | 0.959542 |
14. A computer-implemented method of comprising: as implemented by one or more computing devices configured with specific executable instructions, computing feedback scores associated with pre-defined alternative segments of an individual unfinished work, the pre-defined alternative segments being alternative versions of a portion of the individual unfinished work, wherein each of the pre-defined alternative segments represents one of a beat, a scene or a chapter; generating a comparison of the computed feedback scores associated with the pre-defined alternative segments based at least in part on demographic criteria that divide commentators who provide feedback into groups; and providing data indicative of the comparison to a computing device to present to a user. | 14. A computer-implemented method of comprising: as implemented by one or more computing devices configured with specific executable instructions, computing feedback scores associated with pre-defined alternative segments of an individual unfinished work, the pre-defined alternative segments being alternative versions of a portion of the individual unfinished work, wherein each of the pre-defined alternative segments represents one of a beat, a scene or a chapter; generating a comparison of the computed feedback scores associated with the pre-defined alternative segments based at least in part on demographic criteria that divide commentators who provide feedback into groups; and providing data indicative of the comparison to a computing device to present to a user. 19. The computer-implemented method of claim 14 , wherein the demographic criteria is based at least in part on at least one reputation score associated with a commentator. | 0.731938 |
1. In a computing environment, a method of aggregating context information for messages, the method comprising: receiving a plurality of messages from a computer implemented communication medium, each message including context information conforming to one or more protocols employed by the message; for each of the received messages: processing the message to form a canonical enveloped message, the canonical enveloped message comprising payload data and a header, and wherein processing the message to form a canonical enveloped message further includes creating a context store as a property of the header of the canonical enveloped message for storing the context information of the message in a form that is independent of the one or more protocols employed by the message; at a protocol pipeline comprising a plurality of protocol components processing the canonical enveloped message to extract the context information conforming to the one or more protocols employed by the message and include the extracted context information within the context store of the canonical enveloped message, wherein each portion of the context information is stored in the context store as a context entry that comprises at least a name element to identify the portion, a value element representing the value of the identified portion, and optionally a metadata element that defines any additional information about the identified portion, such that context information for a plurality of protocol components is aggregated using a common format in the context store; and processing the canonical enveloped message at an application, including accessing at least some of the context entries in the context store to retrieve the context information of the message. | 1. In a computing environment, a method of aggregating context information for messages, the method comprising: receiving a plurality of messages from a computer implemented communication medium, each message including context information conforming to one or more protocols employed by the message; for each of the received messages: processing the message to form a canonical enveloped message, the canonical enveloped message comprising payload data and a header, and wherein processing the message to form a canonical enveloped message further includes creating a context store as a property of the header of the canonical enveloped message for storing the context information of the message in a form that is independent of the one or more protocols employed by the message; at a protocol pipeline comprising a plurality of protocol components processing the canonical enveloped message to extract the context information conforming to the one or more protocols employed by the message and include the extracted context information within the context store of the canonical enveloped message, wherein each portion of the context information is stored in the context store as a context entry that comprises at least a name element to identify the portion, a value element representing the value of the identified portion, and optionally a metadata element that defines any additional information about the identified portion, such that context information for a plurality of protocol components is aggregated using a common format in the context store; and processing the canonical enveloped message at an application, including accessing at least some of the context entries in the context store to retrieve the context information of the message. 2. The method of claim 1 , further comprising: for a given protocol component, determining that a given context entry in the context store is for use by a given protocol implemented by the given protocol component and processing the canonical enveloped message using the given context entry. | 0.578606 |
11. A method for generating a trellis coded modulation (TCM) encoded word from an input word, the method comprising: generating, by a first logic branch of a convolutional encoder, a data portion of the encoded word; generating, by a second logic branch of a convolutional encoder coupled in parallel with the first logic branch, a corresponding parity portion of the encoded word sequentially after the generation of the data portion of the encoded word; and holding, by a register comprised within the second logic branch, a final bit of the input word until after the generation of the parity portion of the encoded word, wherein the convolutional encoder is a single convolutional encoder comprised within a trellis coded modulator. | 11. A method for generating a trellis coded modulation (TCM) encoded word from an input word, the method comprising: generating, by a first logic branch of a convolutional encoder, a data portion of the encoded word; generating, by a second logic branch of a convolutional encoder coupled in parallel with the first logic branch, a corresponding parity portion of the encoded word sequentially after the generation of the data portion of the encoded word; and holding, by a register comprised within the second logic branch, a final bit of the input word until after the generation of the parity portion of the encoded word, wherein the convolutional encoder is a single convolutional encoder comprised within a trellis coded modulator. 12. The method of claim 11 , wherein the data portion of the encoded word comprises one bit. | 0.807602 |
8. A computerized method performed by one or more processors, the method comprising: identifying a set of structured data for use in generating a dictionary for a named entity extraction process; identifying a particular collection within the identified structured data to use in the dictionary generation, wherein the particular identified collection includes a plurality of values; for each value in the particular identified collection, identifying at least one variant of the value, wherein each of the at least one variant of the value includes at least a portion of the underlying value, wherein the value includes at least one delimiter, and wherein identifying the at least one variant of the value includes: identifying a first variant based on the full value; identifying a second variant by removing a first suffix from the full value to the first delimiter; and identifying additional variants by removing additional suffixes for each additional delimiter; determining a set of unique variants from the identified at least one variant across each of the values in the particular identified subset; and adding the determined set of unique variants to the generated dictionary, wherein each unique variant added to the generated dictionary is associated with the value from which the unique variant was derived. | 8. A computerized method performed by one or more processors, the method comprising: identifying a set of structured data for use in generating a dictionary for a named entity extraction process; identifying a particular collection within the identified structured data to use in the dictionary generation, wherein the particular identified collection includes a plurality of values; for each value in the particular identified collection, identifying at least one variant of the value, wherein each of the at least one variant of the value includes at least a portion of the underlying value, wherein the value includes at least one delimiter, and wherein identifying the at least one variant of the value includes: identifying a first variant based on the full value; identifying a second variant by removing a first suffix from the full value to the first delimiter; and identifying additional variants by removing additional suffixes for each additional delimiter; determining a set of unique variants from the identified at least one variant across each of the values in the particular identified subset; and adding the determined set of unique variants to the generated dictionary, wherein each unique variant added to the generated dictionary is associated with the value from which the unique variant was derived. 9. The method of claim 8 , wherein the particular collection is associated with an object type, and wherein each unique variant added to the generated dictionary is associated with the object type of the particular collection. | 0.917274 |
4. The personal emotion-based cognitive assistant of claim 2 , further comprising: an output mechanism, which is configured to output via a speaker and a display working visual and audio information, wherein the synchronized visual and audio information observed by the user is the working visual and audio information, wherein the at least one mechanism configured to capture, in real time, the synchronized visual and audio information observed by the user is the working memory which is storing the working visual and audio information displayed on the output mechanism. | 4. The personal emotion-based cognitive assistant of claim 2 , further comprising: an output mechanism, which is configured to output via a speaker and a display working visual and audio information, wherein the synchronized visual and audio information observed by the user is the working visual and audio information, wherein the at least one mechanism configured to capture, in real time, the synchronized visual and audio information observed by the user is the working memory which is storing the working visual and audio information displayed on the output mechanism. 9. The personal emotion-based cognitive assistant system of claim 4 , wherein: the processor is further configured to determine whether the captured emotional state is above another threshold value indicating that the user is confident or evident with the working visual and audio information displayed on the output mechanism, in response to the processor determining that the captured emotional state is above said another threshold value, forming the cognitive module comprising the instinct emotional code generated based on the captured emotional state together with the corresponding displayed working visual and audio information and storing the formed cognitive module in the long term memory area from among the distinct areas of the memory. | 0.82356 |
1. A system that facilitates message filtering, comprising: A computer readable storage medium comprising: a pre-rendering component that receives a message and renders the message into a first format, the received message including one or more compressed images, for each of the one or more compressed images a first hash is generated, wherein the one or more compressed images are rendered in an uncompressed mode, for each of the one or more compressed images rendered in the uncompressed mode a second hash is generated, the first and second hashes are compared to determine if the message contains junk indicia; a converting component that converts the message in the first format into a character-only message and a filtering component that processes the character-only message for predetermined content and routes the received message based upon the predetermined content. | 1. A system that facilitates message filtering, comprising: A computer readable storage medium comprising: a pre-rendering component that receives a message and renders the message into a first format, the received message including one or more compressed images, for each of the one or more compressed images a first hash is generated, wherein the one or more compressed images are rendered in an uncompressed mode, for each of the one or more compressed images rendered in the uncompressed mode a second hash is generated, the first and second hashes are compared to determine if the message contains junk indicia; a converting component that converts the message in the first format into a character-only message and a filtering component that processes the character-only message for predetermined content and routes the received message based upon the predetermined content. 17. The system of claim 1 , the converting component performing word segmentation of the character-only message based upon color and/or visibility of at least one of a character, word and text of the message. | 0.531885 |
1. A method for identifying spam in an email, the method comprising: (a) normalizing an email text morphologically and identifying unique words in the email text; (b) filtering words from the email text, including filtering multi-symbol meaningless human-language words and noise human-language words; (c) determining a number of occurrences of each unique word in the email text; (d) creating a unique numerical identifier for each unique word, the identifier being based on a numerical value corresponding to the unique word; (e) assigning an unique numerical identifier to each unique word in the email text; (f) generating a lexical vector of the email text as a plurality of the assigned identifiers and a frequency of occurrence of each corresponding unique word in the email text; (g) generating a histogram of the lexical vector for each unique numerical identifier of each corresponding unique word in the email text; (h) performing only a single comparison of the histogram of the lexical vector to histograms of lexical vectors of known spam texts; and (i) determining if the email text is spam based on a result of comparison of the histograms. | 1. A method for identifying spam in an email, the method comprising: (a) normalizing an email text morphologically and identifying unique words in the email text; (b) filtering words from the email text, including filtering multi-symbol meaningless human-language words and noise human-language words; (c) determining a number of occurrences of each unique word in the email text; (d) creating a unique numerical identifier for each unique word, the identifier being based on a numerical value corresponding to the unique word; (e) assigning an unique numerical identifier to each unique word in the email text; (f) generating a lexical vector of the email text as a plurality of the assigned identifiers and a frequency of occurrence of each corresponding unique word in the email text; (g) generating a histogram of the lexical vector for each unique numerical identifier of each corresponding unique word in the email text; (h) performing only a single comparison of the histogram of the lexical vector to histograms of lexical vectors of known spam texts; and (i) determining if the email text is spam based on a result of comparison of the histograms. 5. The method of claim 1 , wherein the result of comparison of the histograms is a control value. | 0.629747 |
5. The information management method according to claim 1 , further comprising: setting, when a plurality of paper documents corresponding to the digital document exist, in case of which an attribute of any of the plurality of paper documents corresponding to the digital document is set to indicate a master of the document, an attribute of the digital document corresponding to the paper document to indicate that a change to the digital document is inhibited; and setting, in case of which an attribute of none of the plurality of paper documents corresponding to the digital document is set to indicate a master of the document, the attribute of the digital document corresponding to the paper document to indicate a master of the document. | 5. The information management method according to claim 1 , further comprising: setting, when a plurality of paper documents corresponding to the digital document exist, in case of which an attribute of any of the plurality of paper documents corresponding to the digital document is set to indicate a master of the document, an attribute of the digital document corresponding to the paper document to indicate that a change to the digital document is inhibited; and setting, in case of which an attribute of none of the plurality of paper documents corresponding to the digital document is set to indicate a master of the document, the attribute of the digital document corresponding to the paper document to indicate a master of the document. 6. The information management method according to claim 5 , further comprising managing, when the digital document is the master of the document, coincidence between the content of each of the plurality of paper documents corresponding to the digital document and the content of the digital document. | 0.839037 |
8. A system comprising: one or more computers operable to interact to perform operations comprising: receiving an input string having a plurality of terms, the input string being in a first form, wherein a given sequence of the plurality of terms refers to a geographic feature, wherein the given sequence is annotated with a geographic-feature type selected from a plurality of geographic-feature types each indicating a characteristic of an entity in the physical world corresponding to the geographic feature, and wherein the given sequence is stored in an annotated format with the geographic-feature type in a database of geographic labels prior to receiving the input string; transforming the input string from the first form to a second form, the transforming including: applying one or more rules to the input string to identify one or more terms for translation, the one or more identified terms being fewer than the plurality of terms, wherein at least some of the rules are applied in response to a match between a feature type of the respective rule and the geographic-feature type with which the given sequence is annotated to indicate the characteristic of the corresponding entity in the physical world, translating the identified one or more terms to one or more translated terms in the second form, and transliterating at least some of the remaining terms of the plurality of terms into transliterated terms in the second form, including selecting one or more transliteration rules for application in accordance with the indicated characteristic of the entity, wherein when the given sequence of the plurality of terms is annotated with a first geographic-feature type of the plurality of geographic-feature, a first rule of the one or more rules identifies a specific term in the input string for translation in response to a match between a first feature type of the first rule and the first geographic-feature type, and when the given sequence of the plurality of terms is annotated with a second geographic-feature type of the plurality of geographic-feature types, a second rule of the one or more rules identifies the same specific term in the input string for transliteration in response to a match between a second feature type of the second rule and the second geographic-feature type, wherein the specific term is translated or transliterated to a term having the same grammatical form as the specific term; concatenating at least the translated and transliterated terms to form a hybrid output string in the second form; and storing the hybrid output string in the database of geographic labels; and when map data for a geographic region including the entity is requested for display: (i) retrieving the hybrid output string from the database and (ii) providing, via a network interface, the hybrid output string along with the requested map data for display at a client device. | 8. A system comprising: one or more computers operable to interact to perform operations comprising: receiving an input string having a plurality of terms, the input string being in a first form, wherein a given sequence of the plurality of terms refers to a geographic feature, wherein the given sequence is annotated with a geographic-feature type selected from a plurality of geographic-feature types each indicating a characteristic of an entity in the physical world corresponding to the geographic feature, and wherein the given sequence is stored in an annotated format with the geographic-feature type in a database of geographic labels prior to receiving the input string; transforming the input string from the first form to a second form, the transforming including: applying one or more rules to the input string to identify one or more terms for translation, the one or more identified terms being fewer than the plurality of terms, wherein at least some of the rules are applied in response to a match between a feature type of the respective rule and the geographic-feature type with which the given sequence is annotated to indicate the characteristic of the corresponding entity in the physical world, translating the identified one or more terms to one or more translated terms in the second form, and transliterating at least some of the remaining terms of the plurality of terms into transliterated terms in the second form, including selecting one or more transliteration rules for application in accordance with the indicated characteristic of the entity, wherein when the given sequence of the plurality of terms is annotated with a first geographic-feature type of the plurality of geographic-feature, a first rule of the one or more rules identifies a specific term in the input string for translation in response to a match between a first feature type of the first rule and the first geographic-feature type, and when the given sequence of the plurality of terms is annotated with a second geographic-feature type of the plurality of geographic-feature types, a second rule of the one or more rules identifies the same specific term in the input string for transliteration in response to a match between a second feature type of the second rule and the second geographic-feature type, wherein the specific term is translated or transliterated to a term having the same grammatical form as the specific term; concatenating at least the translated and transliterated terms to form a hybrid output string in the second form; and storing the hybrid output string in the database of geographic labels; and when map data for a geographic region including the entity is requested for display: (i) retrieving the hybrid output string from the database and (ii) providing, via a network interface, the hybrid output string along with the requested map data for display at a client device. 19. The system of claim 8 , wherein transliterating at least some of the remaining terms of the plurality of terms comprises: tokenizing the remaining terms to produce tokens; transliterating a given one of the tokens based on a transliteration rule, wherein the transliteration rule transliterates the given one of the tokens based on an at least part of an adjacent token. | 0.766501 |
1. A method, comprising: receiving enterprise network traffic associated with a particular user; identifying irrelevant documents in the received network traffic using a document filter; developing a personal vocabulary for the particular user based on the enterprise network traffic, wherein the irrelevant documents are not evaluated to develop the personal vocabulary, wherein the personal vocabulary is developed independent of additional users; determining an expertise associated with the particular user based, at least in part, on the personal vocabulary and activity of the additional users; determining a category associated with the particular user, wherein the category is at least partially based on applications used by the particular user; determining areas of interest for the particular user based on the personal vocabulary, the category, and inter-category terms, wherein the inter-category terms are used to link similar categories; determining associations for the particular user in relation to the additional users; and generating a feed based on a portion of the enterprise network traffic and areas of interest for the particular user, wherein the feed is automatically delivered to a subset of the additional users. | 1. A method, comprising: receiving enterprise network traffic associated with a particular user; identifying irrelevant documents in the received network traffic using a document filter; developing a personal vocabulary for the particular user based on the enterprise network traffic, wherein the irrelevant documents are not evaluated to develop the personal vocabulary, wherein the personal vocabulary is developed independent of additional users; determining an expertise associated with the particular user based, at least in part, on the personal vocabulary and activity of the additional users; determining a category associated with the particular user, wherein the category is at least partially based on applications used by the particular user; determining areas of interest for the particular user based on the personal vocabulary, the category, and inter-category terms, wherein the inter-category terms are used to link similar categories; determining associations for the particular user in relation to the additional users; and generating a feed based on a portion of the enterprise network traffic and areas of interest for the particular user, wherein the feed is automatically delivered to a subset of the additional users. 20. The method of claim 1 , wherein at least one of the irrelevant documents includes a JPEG picture. | 0.883562 |
1. A method of identifying regions to merge, in an image of a scene of real world captured by a camera in a handheld device, the method of identifying regions comprising: checking whether a first block, which contains a first region of pixels that are contiguous with one another and comprising a local extrema of intensity in the image, satisfies a predetermined test, for presence along a line, of pixels with intensities binarizable to a common value; marking the first block as pixel-line-present, in a memory, when a result of the checking indicates the predetermined test is satisfied; identifying a second block that is located in the image adjacent to the first block, wherein at least the first block is marked as pixel-line-present; merging a first set of positions indicative of the first region of pixels in the first block with a second set of positions indicative of a second region of pixels in the second block to obtain a merged set of positions in a merged block, when a predetermined rule is satisfied by one or more geometric attributes of the first block and the second block; wherein the first region of pixels and the second region of pixels do not contact one another in the merged block; wherein the merging is performed prior to classification of any pixel in the first region of pixels and in the second region of pixels as text or non-text; and re-doing the checking, on the merged block, to determine whether the merged block satisfies the predetermined test; wherein one or more of the checking, the marking, the identifying, the merging, and the re-doing are performed by at least one processor coupled to the memory. | 1. A method of identifying regions to merge, in an image of a scene of real world captured by a camera in a handheld device, the method of identifying regions comprising: checking whether a first block, which contains a first region of pixels that are contiguous with one another and comprising a local extrema of intensity in the image, satisfies a predetermined test, for presence along a line, of pixels with intensities binarizable to a common value; marking the first block as pixel-line-present, in a memory, when a result of the checking indicates the predetermined test is satisfied; identifying a second block that is located in the image adjacent to the first block, wherein at least the first block is marked as pixel-line-present; merging a first set of positions indicative of the first region of pixels in the first block with a second set of positions indicative of a second region of pixels in the second block to obtain a merged set of positions in a merged block, when a predetermined rule is satisfied by one or more geometric attributes of the first block and the second block; wherein the first region of pixels and the second region of pixels do not contact one another in the merged block; wherein the merging is performed prior to classification of any pixel in the first region of pixels and in the second region of pixels as text or non-text; and re-doing the checking, on the merged block, to determine whether the merged block satisfies the predetermined test; wherein one or more of the checking, the marking, the identifying, the merging, and the re-doing are performed by at least one processor coupled to the memory. 11. The method of claim 1 wherein: a region Q i in the image is determined by comparisons between an intensity i used as a threshold and intensities of a plurality of pixels included in said region Q i ; said region Q i comprises a local extrema in the intensity i in said image; and a number of pixels in said region Q i remains within a predetermined range relative to changes in the intensity i across a range i−Δ to i+Δ, with a local minima in a ratio [Q i−Δ −Q i+Δ ]/Q i occurring at the intensity i. | 0.54596 |
1. A method comprising: selecting a plurality of predetermined demographic groups including externally selected characteristics including historical data from a plurality of actual viewers and historical actual electronic program guide (EPG) data to associate viewers with; recording a viewer's monitor behavior with data item variables including watched channel, watching start time, at least one of watching date and watching duration, a first ratio of time watched to time available for at least one non-hopping program, and a second ratio of time watched to time available for at least one program with hopping, wherein hopping represents an act of leaving and returning to the same program, wherein the first ratio exclusively corresponds to non-hopped programs and said second ratio exclusively corresponds to hopped programs; associating a particular demographic group of the plurality of demographic groups with the viewer; from a server-side system, inputting historical data information regarding demographic information tagged to the viewer for the viewer's demographic group; generating preferred program guide information based on the historical data information for the viewer's demographic group and based on bias metrics; inputting the preferred program guide information for the viewer's demographic group; at a client side system, associating the preferred program guide information with the viewer's monitor behavior; and defining therefrom a knowledge base with demographic group cluster information of the viewer in terms of statistical state machine transition models. | 1. A method comprising: selecting a plurality of predetermined demographic groups including externally selected characteristics including historical data from a plurality of actual viewers and historical actual electronic program guide (EPG) data to associate viewers with; recording a viewer's monitor behavior with data item variables including watched channel, watching start time, at least one of watching date and watching duration, a first ratio of time watched to time available for at least one non-hopping program, and a second ratio of time watched to time available for at least one program with hopping, wherein hopping represents an act of leaving and returning to the same program, wherein the first ratio exclusively corresponds to non-hopped programs and said second ratio exclusively corresponds to hopped programs; associating a particular demographic group of the plurality of demographic groups with the viewer; from a server-side system, inputting historical data information regarding demographic information tagged to the viewer for the viewer's demographic group; generating preferred program guide information based on the historical data information for the viewer's demographic group and based on bias metrics; inputting the preferred program guide information for the viewer's demographic group; at a client side system, associating the preferred program guide information with the viewer's monitor behavior; and defining therefrom a knowledge base with demographic group cluster information of the viewer in terms of statistical state machine transition models. 12. The method according to claim 1 , wherein the data items have a probability function with a confidence level, the method further comprising: updating the historical data information upon determining that a given data item has a probability function with a higher confidence level than a previous data item. | 0.575012 |
3. The method of claim 2 wherein rendering the graphical rendition in each frame of a first series of image frames as a rendered image depicting the active movements further comprises depicting the active movements by emulating the user performing the speech conveyed by the expressive input, the expressive input contained in an input stream including the indication of active movements. | 3. The method of claim 2 wherein rendering the graphical rendition in each frame of a first series of image frames as a rendered image depicting the active movements further comprises depicting the active movements by emulating the user performing the speech conveyed by the expressive input, the expressive input contained in an input stream including the indication of active movements. 4. The method of claim 3 further comprising: performing feature extraction on the input stream to derive facial features; deriving, from the input stream, facial features including a perspective angle and jaw movements corresponding to the spoken verbiage; and computing, from the facial features, the active movements. | 0.868179 |
11. A network-based computer system for facilitating share sites, comprising: one or more servers comprising computer processors configured to receive registrations from users to set up share sites and to become owners of the share sites, to enable the users to send emails to invite people to become members of their respective share sites, and to receive uploads of at least one image or video clip from the users, wherein the one or more servers are configured to store one or more spam detection rules in a spam intelligence module and to detect potential spam emails among the emails sent by the users based on the one or more spam detection rules, wherein the one or more servers are configured to store one or more false alarm reduction rules in the spam intelligence module, to automatically detect behaviors of one or more senders of the potential spam emails at the share-site, and to identify false positive emails in the potential spam emails based on the one or more false alarm reduction rules and the behaviors of the one or more senders of the potential spam emails at the share-site, which comprises at least determining if the one or more senders of the potential spam emails have uploaded at least one image or video clip to the network-based computer system, wherein the false positive emails are removed from the potential spam emails to produce a list of verified spam emails, wherein the one or more servers are configured to identify a first sender of the list of verified spam emails as a spammer and to prohibit the spammer from sending emails from one or more share sites owned by the spammer. | 11. A network-based computer system for facilitating share sites, comprising: one or more servers comprising computer processors configured to receive registrations from users to set up share sites and to become owners of the share sites, to enable the users to send emails to invite people to become members of their respective share sites, and to receive uploads of at least one image or video clip from the users, wherein the one or more servers are configured to store one or more spam detection rules in a spam intelligence module and to detect potential spam emails among the emails sent by the users based on the one or more spam detection rules, wherein the one or more servers are configured to store one or more false alarm reduction rules in the spam intelligence module, to automatically detect behaviors of one or more senders of the potential spam emails at the share-site, and to identify false positive emails in the potential spam emails based on the one or more false alarm reduction rules and the behaviors of the one or more senders of the potential spam emails at the share-site, which comprises at least determining if the one or more senders of the potential spam emails have uploaded at least one image or video clip to the network-based computer system, wherein the false positive emails are removed from the potential spam emails to produce a list of verified spam emails, wherein the one or more servers are configured to identify a first sender of the list of verified spam emails as a spammer and to prohibit the spammer from sending emails from one or more share sites owned by the spammer. 17. The network-based computer system of claim 11 , wherein the one or more servers are configured to determine if the one or more senders of the potential spam emails have ordered at least one product or service from the network-based computer system. | 0.500591 |
8. The method of claim 1 , wherein upon receiving the user-selected object type the computer system identifies a set of attributes associated with the user-selected object type, and wherein the computer system populates the input control with the set of attributes for the user to select between. | 8. The method of claim 1 , wherein upon receiving the user-selected object type the computer system identifies a set of attributes associated with the user-selected object type, and wherein the computer system populates the input control with the set of attributes for the user to select between. 10. The method of claim 8 , wherein the computer system identifies the set of attributes by requesting that the first application program identify the set of attributes associated with the user-selected object type. | 0.915907 |
1. A data converting apparatus comprising: a storage unit that stores encoded meta-definition information that assigns a metadata code as a unique code to an element making up metadata in meta-definition information that defines metadata indicative of a property related to data of a conversion source and a conversion destination, a data converting function that converts conversion source data having a property prescribed by the metadata for the conversion source into conversion destination data having a property prescribed by the metadata for the conversion destination, a conversion rule table that assigns the data converting function according to a combination of a metadata code for the conversion source and a metadata code for the conversion destination, and a conversion rule that correlates with each of the conversion rule tables, a relevant metadata code as a conversion rule code; an input unit that receives input of data to be converted; a detecting unit that refers to the encoded meta-definition information stored in the storage unit and detects the metadata codes for the conversion source and the conversion destination for which the conversion rule code matches between the conversion source and the conversion destination; a determining unit that determines whether the detected metadata codes for the conversion source and for the conversion destination match; a converting function specifying unit that, by referring to a conversion rule stored in the storage unit and based on the determination result obtained by the determining unit, specifies the data converting function, according to the combination of the metadata code for the conversion source and the metadata code for the conversion destination; and a converting unit that, by using the data converting function specified by the converting function specifying unit, converts the conversion source data, which is the data to be converted, to have a property prescribed by metadata for the conversion destination. | 1. A data converting apparatus comprising: a storage unit that stores encoded meta-definition information that assigns a metadata code as a unique code to an element making up metadata in meta-definition information that defines metadata indicative of a property related to data of a conversion source and a conversion destination, a data converting function that converts conversion source data having a property prescribed by the metadata for the conversion source into conversion destination data having a property prescribed by the metadata for the conversion destination, a conversion rule table that assigns the data converting function according to a combination of a metadata code for the conversion source and a metadata code for the conversion destination, and a conversion rule that correlates with each of the conversion rule tables, a relevant metadata code as a conversion rule code; an input unit that receives input of data to be converted; a detecting unit that refers to the encoded meta-definition information stored in the storage unit and detects the metadata codes for the conversion source and the conversion destination for which the conversion rule code matches between the conversion source and the conversion destination; a determining unit that determines whether the detected metadata codes for the conversion source and for the conversion destination match; a converting function specifying unit that, by referring to a conversion rule stored in the storage unit and based on the determination result obtained by the determining unit, specifies the data converting function, according to the combination of the metadata code for the conversion source and the metadata code for the conversion destination; and a converting unit that, by using the data converting function specified by the converting function specifying unit, converts the conversion source data, which is the data to be converted, to have a property prescribed by metadata for the conversion destination. 14. The data converting apparatus according to claim 1 , comprising: a specification-definition information acquiring unit that acquires specification definition information that defines a specification related to the metadata and defines the data converting function; a first setting unit that sets a metadata encoding table that correlates with the metadata, a metadata code specifying the metadata in the specification definition information acquired by the specification-definition information acquiring unit; a second setting unit that sets the conversion rule table; and a constructing unit that constructs the conversion rule. | 0.570663 |
1. A processor comprising: a front end unit including an instruction fetch unit and a decode unit; an execution engine coupled to the front end unit; and a memory unit coupled to the execution engine and including a first cache, wherein the processor is to read a first portion of a plurality of portions of a data word from a first portion of the first cache and read a second portion of the plurality of portions from a second memory, wherein the first portion is to be processed before the second portion, and the second memory is distinct from the first cache based on at least a physical attribute. | 1. A processor comprising: a front end unit including an instruction fetch unit and a decode unit; an execution engine coupled to the front end unit; and a memory unit coupled to the execution engine and including a first cache, wherein the processor is to read a first portion of a plurality of portions of a data word from a first portion of the first cache and read a second portion of the plurality of portions from a second memory, wherein the first portion is to be processed before the second portion, and the second memory is distinct from the first cache based on at least a physical attribute. 11. The processor of claim 1 , wherein the processor comprises a system on chip (SoC), the SoC further including a graphics processor. | 0.612694 |
1. A method for establishing an applicable local time zone of a web browser in a computing environment by a processor device, comprising: querying a plurality of time zone offsets over a predetermined period of time to obtain a listing of possible time zones; selecting one of the listing of possible time zones matching a polled absolute coordinated universal time (UTC) offset; assigning a plurality of numerical weights to the selected ones of the listing of possible time zones according to a weighting process based on the matching polled absolute UTC offset, a matching daylight savings observance type, a matching Hyper-Text Transfer Protocol (HTTP) accept-language header, and a human population size; combining each of the assigned plurality of numerical weights to generate a combined numerical weight for the selected ones of the listing of possible time zones; sorting the listing of possible time zones based on the combined numerical weight; and selecting one of the listing of sorted possible time zones having a highest combined numerical weight of the plurality of assigned numerical weights to format a time stamped output. | 1. A method for establishing an applicable local time zone of a web browser in a computing environment by a processor device, comprising: querying a plurality of time zone offsets over a predetermined period of time to obtain a listing of possible time zones; selecting one of the listing of possible time zones matching a polled absolute coordinated universal time (UTC) offset; assigning a plurality of numerical weights to the selected ones of the listing of possible time zones according to a weighting process based on the matching polled absolute UTC offset, a matching daylight savings observance type, a matching Hyper-Text Transfer Protocol (HTTP) accept-language header, and a human population size; combining each of the assigned plurality of numerical weights to generate a combined numerical weight for the selected ones of the listing of possible time zones; sorting the listing of possible time zones based on the combined numerical weight; and selecting one of the listing of sorted possible time zones having a highest combined numerical weight of the plurality of assigned numerical weights to format a time stamped output. 3. The method of claim 1 , further including merging some of the listing of possible time zones by grouping those of the listing of possible time zones having shared daylight saving transition rules over the predetermined period of time. | 0.639977 |
1. The integrated circuit chip comprising programmable intelligent search memory for content search wherein said programmable intelligent search memory performs regular expression based search and wherein said regular expression comprises complex symbols, said programmable intelligent search memory for content search using one or more regular expressions, said one or more regular expressions comprising one or more symbols or characters and further comprising one or more complex symbols, said one or more regular expressions converted into one or more finite state automata representing the functionality of said one or more regular expressions for programming in said programmable intelligent search memory, said one or more finite state automata comprising a plurality of states, said plurality of states derived from said one or more symbols or characters of said one or more regular expressions, said content comprising one or more input symbols provided as input to said programmable intelligent search memory, said programmable intelligent search memory comprising at least one of each of: a. a symbol memory circuit to store said one or more symbols; b. a complex symbol memory circuit to store said one or more complex symbols; c. a complex symbol evaluation circuit coupled to said complex symbol memory circuit to evaluate match of said one or more complex symbols stored in said complex symbol memory circuit with said one or more input symbols of said content; d. a symbol evaluation circuit coupled to said symbol memory circuit to evaluate match of said one or more symbols stored in said symbol memory circuit with said one or more input symbols of said content; e. a state dependent vector memory circuit to store state transition controls for said one or more finite state automata; f. a current state vector memory circuit to store said plurality of states; and g. a state transition circuit coupled to said symbol evaluation circuit, said complex symbol evaluation circuit, said current state vector memory circuit and said state dependent vector memory circuit to perform state transition from one or more first states to one or more second states of said plurality of states of said one or more finite state automata. | 1. The integrated circuit chip comprising programmable intelligent search memory for content search wherein said programmable intelligent search memory performs regular expression based search and wherein said regular expression comprises complex symbols, said programmable intelligent search memory for content search using one or more regular expressions, said one or more regular expressions comprising one or more symbols or characters and further comprising one or more complex symbols, said one or more regular expressions converted into one or more finite state automata representing the functionality of said one or more regular expressions for programming in said programmable intelligent search memory, said one or more finite state automata comprising a plurality of states, said plurality of states derived from said one or more symbols or characters of said one or more regular expressions, said content comprising one or more input symbols provided as input to said programmable intelligent search memory, said programmable intelligent search memory comprising at least one of each of: a. a symbol memory circuit to store said one or more symbols; b. a complex symbol memory circuit to store said one or more complex symbols; c. a complex symbol evaluation circuit coupled to said complex symbol memory circuit to evaluate match of said one or more complex symbols stored in said complex symbol memory circuit with said one or more input symbols of said content; d. a symbol evaluation circuit coupled to said symbol memory circuit to evaluate match of said one or more symbols stored in said symbol memory circuit with said one or more input symbols of said content; e. a state dependent vector memory circuit to store state transition controls for said one or more finite state automata; f. a current state vector memory circuit to store said plurality of states; and g. a state transition circuit coupled to said symbol evaluation circuit, said complex symbol evaluation circuit, said current state vector memory circuit and said state dependent vector memory circuit to perform state transition from one or more first states to one or more second states of said plurality of states of said one or more finite state automata. 2. The integrated circuit chip of claim 1 , wherein the symbol memory circuit, the complex symbol memory circuit, the state dependent vector memory circuit, and the current state vector memory circuit of the programmable intelligent search memory comprises static random access memory circuits. | 0.66016 |
10. A machine learning method comprising: receiving, from a user device, a sequence of at least one letter; determining location information associated with the user device; mapping the received sequence of at least one letter and the location information with a database of multiple terms, the database relating a term to a stored sequence of at least one letter and a location range based on a historical correlation between the term and the stored sequence of at least one letter in the location range; providing a candidate term out of the multiple terms as corresponding to the received sequence of at least one letter based on the mapping; displaying the candidate term as corresponding to the received sequence of at least one letter; receiving a user feedback on the candidate term; and updating the database based on the user feedback. | 10. A machine learning method comprising: receiving, from a user device, a sequence of at least one letter; determining location information associated with the user device; mapping the received sequence of at least one letter and the location information with a database of multiple terms, the database relating a term to a stored sequence of at least one letter and a location range based on a historical correlation between the term and the stored sequence of at least one letter in the location range; providing a candidate term out of the multiple terms as corresponding to the received sequence of at least one letter based on the mapping; displaying the candidate term as corresponding to the received sequence of at least one letter; receiving a user feedback on the candidate term; and updating the database based on the user feedback. 16. The machine learning method of claim 10 , wherein the database includes a geographic word stock related to a location range, and the geographic word stock is constructed by: determining a utilization frequency of a geographic word in the location range; determining that the utilization frequency of the geographic word is greater than a threshold value; and storing the geographic word as corresponding to a corresponding stored sequence of at least one letter in the database. | 0.5 |
9. A method comprising: receiving a user-submitted query originating from a user; determining whether the user-submitted query is a difficult query, wherein a difficult query is a query that will not return relevant or authoritative results; in an event that the user-submitted query is not a difficult query: sending the user-submitted query to a search engine; receiving search results associated with the user-submitted query from the search engine; and presenting the search results associated with the user-submitted query; and in an event that the user-submitted query is a difficult query: identifying, without further input from the user, a plurality of candidate queries; for each candidate query, without further input from the user: generating a feature vector that includes three or more features, each of the three or more features being individual components of the feature vector, each feature reflecting a measurement of effectiveness of the candidate query with respect to the user-submitted query, the measurement of effectiveness of the candidate query based, at least in part, on search results of the candidate query, the three or more features including an estimated normalized discounted cumulative gain; and calculating a usefulness probability value based at least in part on the feature vector, wherein the usefulness probability value reflects an estimated quality of the search results for the candidate query with respect to the user-submitted query; rank ordering the candidate queries based on the usefulness probability values; and suggesting one or more of the top-ranked candidate queries as alternate queries for the user-submitted query; in the event that the user-submitted query is a difficult query: receiving a user selection of a particular query selected from the user-submitted query and the alternate queries that are suggested; and presenting the search results associated with the particular query. | 9. A method comprising: receiving a user-submitted query originating from a user; determining whether the user-submitted query is a difficult query, wherein a difficult query is a query that will not return relevant or authoritative results; in an event that the user-submitted query is not a difficult query: sending the user-submitted query to a search engine; receiving search results associated with the user-submitted query from the search engine; and presenting the search results associated with the user-submitted query; and in an event that the user-submitted query is a difficult query: identifying, without further input from the user, a plurality of candidate queries; for each candidate query, without further input from the user: generating a feature vector that includes three or more features, each of the three or more features being individual components of the feature vector, each feature reflecting a measurement of effectiveness of the candidate query with respect to the user-submitted query, the measurement of effectiveness of the candidate query based, at least in part, on search results of the candidate query, the three or more features including an estimated normalized discounted cumulative gain; and calculating a usefulness probability value based at least in part on the feature vector, wherein the usefulness probability value reflects an estimated quality of the search results for the candidate query with respect to the user-submitted query; rank ordering the candidate queries based on the usefulness probability values; and suggesting one or more of the top-ranked candidate queries as alternate queries for the user-submitted query; in the event that the user-submitted query is a difficult query: receiving a user selection of a particular query selected from the user-submitted query and the alternate queries that are suggested; and presenting the search results associated with the particular query. 12. One or more non-transitory computer storage media encoded with computer-executable instructions that, when executed, configure a computer system to perform a method as recited in claim 9 . | 0.545918 |
8. A computer implemented method for processing a hierarchically structured document, comprising the steps of: creating a first dictionary having a first set of information including key-value pairs when processing a predetermined hierarchical level of the document; creating a first dictionary reference to the first dictionary for the predetermined hierarchical level; processing a structure element of a subsequent hierarchical level of the document, wherein said subsequent hierarchical level is lower in the hierarchical structure of the document than the predetermined hierarchical level; copying the first dictionary reference to a second dictionary reference for the structure portion of the subsequent hierarchical level; processing a content portion of the subsequent hierarchical level; copying the second dictionary reference to a third dictionary reference for the content portion of the subsequent hierarchical level; creating a second dictionary for the subsequent hierarchical level, when processing the content portion of the subsequent hierarchical level, said second dictionary having a second set of information including key-value pairs; changing the third dictionary reference to refer first to the second dictionary and subsequently to the first dictionary; and searching for an entry in a dictionary when processing content of the subsequent hierarchical level by searching the second dictionary by locating the second dictionary using the third reference and then searching the first dictionary using the third reference, without referring to the first reference. | 8. A computer implemented method for processing a hierarchically structured document, comprising the steps of: creating a first dictionary having a first set of information including key-value pairs when processing a predetermined hierarchical level of the document; creating a first dictionary reference to the first dictionary for the predetermined hierarchical level; processing a structure element of a subsequent hierarchical level of the document, wherein said subsequent hierarchical level is lower in the hierarchical structure of the document than the predetermined hierarchical level; copying the first dictionary reference to a second dictionary reference for the structure portion of the subsequent hierarchical level; processing a content portion of the subsequent hierarchical level; copying the second dictionary reference to a third dictionary reference for the content portion of the subsequent hierarchical level; creating a second dictionary for the subsequent hierarchical level, when processing the content portion of the subsequent hierarchical level, said second dictionary having a second set of information including key-value pairs; changing the third dictionary reference to refer first to the second dictionary and subsequently to the first dictionary; and searching for an entry in a dictionary when processing content of the subsequent hierarchical level by searching the second dictionary by locating the second dictionary using the third reference and then searching the first dictionary using the third reference, without referring to the first reference. 9. A method according to claim 8, further comprising the steps of: completing processing of the content portion of the subsequent hierarchical level; determining if the content portion of the subsequent hierarchical level defined a dictionary; and copying the third dictionary reference to the second dictionary reference, only when the content portion of the subsequent hierarchical level has been determined to define a dictionary. | 0.582681 |
34. A computer system comprising: one or more memories configured for storing executable instructions; and one or more processors configured for executing the instructions, wherein the instructions include instructions to: receive a search query; retrieve a set of documents relevant to the search query, each document having a relevance score; determine, for each document in the set of documents, whether the document has been identified as a spam document; down-weight the relevance score of the document in response to a document being identified as a spam document; and organize the set of documents by their relevance scores, wherein the relevance scores by which the documents are organized include down-weighted relevance scores for documents that have been identified as spam documents, wherein whether the document has been identified as a spam document is based on: determining, for a document that contains a first phrase, a number of related phrases related to the first phrase expected to be present in the document; determining for the document, and for the first phrase in the document, an actual number of related phrases present in the document; and identifying the document as a spam document by comparing the actual number of related phrases present in the document with the expected number of related phrases, wherein determining the number of related phrases expected to be present in the document includes: traversing an index of a plurality of documents; for each of the indexed documents, determining a set of phrases in the document, and for each phrase in the set, determining a number of related phrases also in the document; and determining the expected number of related phrases based on the determined number of related phrases across the traversed documents. | 34. A computer system comprising: one or more memories configured for storing executable instructions; and one or more processors configured for executing the instructions, wherein the instructions include instructions to: receive a search query; retrieve a set of documents relevant to the search query, each document having a relevance score; determine, for each document in the set of documents, whether the document has been identified as a spam document; down-weight the relevance score of the document in response to a document being identified as a spam document; and organize the set of documents by their relevance scores, wherein the relevance scores by which the documents are organized include down-weighted relevance scores for documents that have been identified as spam documents, wherein whether the document has been identified as a spam document is based on: determining, for a document that contains a first phrase, a number of related phrases related to the first phrase expected to be present in the document; determining for the document, and for the first phrase in the document, an actual number of related phrases present in the document; and identifying the document as a spam document by comparing the actual number of related phrases present in the document with the expected number of related phrases, wherein determining the number of related phrases expected to be present in the document includes: traversing an index of a plurality of documents; for each of the indexed documents, determining a set of phrases in the document, and for each phrase in the set, determining a number of related phrases also in the document; and determining the expected number of related phrases based on the determined number of related phrases across the traversed documents. 36. The computer system of claim 34 , wherein whether the document has been identified as a spam document is further based on: determining, for a second phrase contained in the document, a number of the related phrases related to a second phrase expected to be present in the document; determining for the document, and for the second phrase in the document, an actual number of related phrases present in the document; determining, for a third phrase contained in the document, a number of the related phrases related to a third phrase expected to be present in the document; determining for the document, and for the third phrase in the document, an actual number of related phrases present in the document; identifying the document as a spam document where, for each of the first phrase, the second phrase, and the third phrase, the actual number of related phrases present in the document exceeds the expected number of related phrases based on a threshold. | 0.50538 |
19. A system comprising: a processing unit coupled to a memory through a bus; and a process executed from the memory by the processing unit to cause the processing unit to: prune redundancy of instances in a plurality of speech segments, wherein the redundancy criterion is based on a similarity measure between feature vectors derived from a machine perception transformation of time-domain samples corresponding to the instances in the plurality of speech segments, wherein the instances subjected to redundancy pruning are clustered together with feature vectors discernably separated from each other in the machine perception transformation and wherein the machine perception transformation is correlated with human perception by using the time-domain samples retaining both amplitude and phase information of the speech segments, which were provided in sound data for a speech synthesis system. | 19. A system comprising: a processing unit coupled to a memory through a bus; and a process executed from the memory by the processing unit to cause the processing unit to: prune redundancy of instances in a plurality of speech segments, wherein the redundancy criterion is based on a similarity measure between feature vectors derived from a machine perception transformation of time-domain samples corresponding to the instances in the plurality of speech segments, wherein the instances subjected to redundancy pruning are clustered together with feature vectors discernably separated from each other in the machine perception transformation and wherein the machine perception transformation is correlated with human perception by using the time-domain samples retaining both amplitude and phase information of the speech segments, which were provided in sound data for a speech synthesis system. 21. The system of claim 19 wherein the feature vectors incorporate phase information of the instances. | 0.796393 |
1. A process for retrieving and viewing partial content of a server stored document on a mobile communication device, comprising: extracting informational entities from said document within said server; populating a model of said document within said server with elements corresponding to said informational entities; detecting navigational entities within said informational entities and in response storing within said server source and target destinations associated with said navigational entities; assigning an identifier to each of said source and target destinations within said model; paginating said model within said server into a plurality of segments identified by respective index values, comprising updating each said identifier with an attribute containing a corresponding one of said index values; generating output data for delivery to said mobile communication device by traversing through said elements in said model and recording each element as an equivalent command containing content and document characteristics; sending a first request from the mobile communication device to the server to display said document; in response to receiving said first request transmitting a first segment of said output data from said server to said mobile communication device; parsing said output data within said mobile communication device and executing each said equivalent command to thereby display said content of said first segment of the document according to said document characteristics comprising any of said navigational entities contained within said first segment; in response to user selection of a navigational entity displayed on said mobile communication device sending a further request to said server containing the identifier and index value corresponding to said navigational entity; in response to receiving said further request transmitting a further segment of said output data from said server to said mobile communication device from a location in said model corresponding to said index value; parsing said further segment of output data within said mobile communication device and executing each said equivalent command to thereby display said content of said further segment of the document according to said document characteristics; detecting within said mobile communication device any skipped content between said first and further segment and providing a visual indication of said skipped content on said mobile communication device, wherein said visual indication of said skipped content includes a horizontal bar indicator between said first and further segment displayed on said mobile communication device; and; calculating and displaying size of said skipped content within said horizontal bar indicator. | 1. A process for retrieving and viewing partial content of a server stored document on a mobile communication device, comprising: extracting informational entities from said document within said server; populating a model of said document within said server with elements corresponding to said informational entities; detecting navigational entities within said informational entities and in response storing within said server source and target destinations associated with said navigational entities; assigning an identifier to each of said source and target destinations within said model; paginating said model within said server into a plurality of segments identified by respective index values, comprising updating each said identifier with an attribute containing a corresponding one of said index values; generating output data for delivery to said mobile communication device by traversing through said elements in said model and recording each element as an equivalent command containing content and document characteristics; sending a first request from the mobile communication device to the server to display said document; in response to receiving said first request transmitting a first segment of said output data from said server to said mobile communication device; parsing said output data within said mobile communication device and executing each said equivalent command to thereby display said content of said first segment of the document according to said document characteristics comprising any of said navigational entities contained within said first segment; in response to user selection of a navigational entity displayed on said mobile communication device sending a further request to said server containing the identifier and index value corresponding to said navigational entity; in response to receiving said further request transmitting a further segment of said output data from said server to said mobile communication device from a location in said model corresponding to said index value; parsing said further segment of output data within said mobile communication device and executing each said equivalent command to thereby display said content of said further segment of the document according to said document characteristics; detecting within said mobile communication device any skipped content between said first and further segment and providing a visual indication of said skipped content on said mobile communication device, wherein said visual indication of said skipped content includes a horizontal bar indicator between said first and further segment displayed on said mobile communication device; and; calculating and displaying size of said skipped content within said horizontal bar indicator. 7. The process of claim 1 , wherein said paginating is performed by said server upon receipt of said first request. | 0.514226 |
1. A text mining apparatus for performing text mining, comprising: at least one input that receives a first text data and a second text data, each word of the first and second text data has a confidence; and a processor configured to calculate a mutual information amount I(w i , w j ) at least based on a frequency of appearance of word w i in the first text data N 1st (w i ), a frequency of appearance of word w j in the second text data N 2nd (w j ), and a frequency of co-appearance of w i and w j in both text data N 1st,2nd (w i ,w j ) using the confidence of w j , and the confidence of and use the mutual information amount I(w i , w j ) to calculate degrees to which w i and w j correspond to inherent portions of the first and second text data, wherein N 1 st ( w i ) = ∑ l R 1 st ( w i , l ) , [ Equation A ] N 2 nd ( w j ) = ∑ l R 2 nd ( w j , l ) , [ Equation B ] N 1 st , 2 nd ( w i , w j ) = ∑ l R 1 st ( w i , l ) R 2 nd ( w j , l ) , [ Equation C ] R 1st (w i ,l) indicates a confidence of w i for record l, R 2nd (w j ,l) indicates a confidence of w j for record l. | 1. A text mining apparatus for performing text mining, comprising: at least one input that receives a first text data and a second text data, each word of the first and second text data has a confidence; and a processor configured to calculate a mutual information amount I(w i , w j ) at least based on a frequency of appearance of word w i in the first text data N 1st (w i ), a frequency of appearance of word w j in the second text data N 2nd (w j ), and a frequency of co-appearance of w i and w j in both text data N 1st,2nd (w i ,w j ) using the confidence of w j , and the confidence of and use the mutual information amount I(w i , w j ) to calculate degrees to which w i and w j correspond to inherent portions of the first and second text data, wherein N 1 st ( w i ) = ∑ l R 1 st ( w i , l ) , [ Equation A ] N 2 nd ( w j ) = ∑ l R 2 nd ( w j , l ) , [ Equation B ] N 1 st , 2 nd ( w i , w j ) = ∑ l R 1 st ( w i , l ) R 2 nd ( w j , l ) , [ Equation C ] R 1st (w i ,l) indicates a confidence of w i for record l, R 2nd (w j ,l) indicates a confidence of w j for record l. 5. The text mining apparatus according to claim 1 , the processor further configured to separately perform text mining of the inherent portions of the first and second text data. | 0.733453 |
8. An apparatus comprising: a processor; and a compiler comprising: a parse engine accessible to the processor to receive input script; a standard language grammar module accessible to the processor to define features of a programming language of the input script; an active profile module accessible to the processor to define a sequence of namespaces; and a language metadata provider accessible to the processor to: modify language metadata of the programming language, the language metadata specifying runtime characteristics of the programming language; and modify one or more of the namespaces based on respective modifications to the language metadata, each of the respective modifications being associated with a particular scope indicating one or more sessions for which to apply a respective modification. | 8. An apparatus comprising: a processor; and a compiler comprising: a parse engine accessible to the processor to receive input script; a standard language grammar module accessible to the processor to define features of a programming language of the input script; an active profile module accessible to the processor to define a sequence of namespaces; and a language metadata provider accessible to the processor to: modify language metadata of the programming language, the language metadata specifying runtime characteristics of the programming language; and modify one or more of the namespaces based on respective modifications to the language metadata, each of the respective modifications being associated with a particular scope indicating one or more sessions for which to apply a respective modification. 13. The apparatus of claim 8 , wherein the language metadata provider includes logic for navigating and manipulating the language metadata. | 0.89426 |
20. The system of claim 17 wherein the system is further configured to: receive the new content items from heterogeneous data sources; and categorize the new content items. | 20. The system of claim 17 wherein the system is further configured to: receive the new content items from heterogeneous data sources; and categorize the new content items. 21. The system of claim 20 wherein the heterogeneous data sources include at least two from the group of a news article post, a news feed, a social feed, a blog post, a micro-blog post, a photo, a video, an audio, an email message, and a text based message. | 0.915576 |
15. A computer-readable memory storage device having stored thereon: a data structure that comprises at least some data defined according to an extensible markup language (XML) schema, comprising: a first set of data that associates the data structure with a software component programmed in a dynamically-typed programming language; a second set of data comprising descriptive information with respect to the software component; a third set of data comprising an explicit data type identification for the software component; and a programming environment configured to: provide a design surface comprising icons representing other software components also programmed in a dynamically-typed programming language; access the data structure upon selection of an icon representing the software component based on the first set of data and connection of the icon to at least one other icon of the design surface, uses the second set of data to provide descriptive information, and validate usage of the software component based on the data type identification in the third set of data to provide a type system for the software component that does not rely upon inference by enforcing at least one constraint setting a default value and validating at least one type corresponding to at least one date value of the software component at runtime during execution of the software component and a runtime environment configured to validate execution of the software component at runtime by performing enhanced type matching during execution, including inserting executable code into the selected programming language component that converts one date type to an appropriate type for input or output. | 15. A computer-readable memory storage device having stored thereon: a data structure that comprises at least some data defined according to an extensible markup language (XML) schema, comprising: a first set of data that associates the data structure with a software component programmed in a dynamically-typed programming language; a second set of data comprising descriptive information with respect to the software component; a third set of data comprising an explicit data type identification for the software component; and a programming environment configured to: provide a design surface comprising icons representing other software components also programmed in a dynamically-typed programming language; access the data structure upon selection of an icon representing the software component based on the first set of data and connection of the icon to at least one other icon of the design surface, uses the second set of data to provide descriptive information, and validate usage of the software component based on the data type identification in the third set of data to provide a type system for the software component that does not rely upon inference by enforcing at least one constraint setting a default value and validating at least one type corresponding to at least one date value of the software component at runtime during execution of the software component and a runtime environment configured to validate execution of the software component at runtime by performing enhanced type matching during execution, including inserting executable code into the selected programming language component that converts one date type to an appropriate type for input or output. 18. The one or more computer-readable memory storage device of claim 15 wherein the third set of data comprises at least one of a constraint associated with a value, at least one of default data for a value, at least one of type information for a value, or data that indicates whether a value is required, or any combination of a constraint associated with a value, default data for a value, type system information for a value, or at least one of data that indicates whether a value is required. | 0.5 |
19. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: identifying two or more consecutive terms in a search query; determining a first quantity of search results that (i) are responsive to the search query, and (ii) have been selected by a user; determining a second quantity of search results that (i) are responsive to the search query, (ii) have been selected by the user, and (iii) have summaries that include the two or more consecutive terms; determining a value using the first quantity and the second quantity; and determining a likelihood that the two or more consecutive terms represent a compound based on the value. | 19. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: identifying two or more consecutive terms in a search query; determining a first quantity of search results that (i) are responsive to the search query, and (ii) have been selected by a user; determining a second quantity of search results that (i) are responsive to the search query, (ii) have been selected by the user, and (iii) have summaries that include the two or more consecutive terms; determining a value using the first quantity and the second quantity; and determining a likelihood that the two or more consecutive terms represent a compound based on the value. 21. The medium of claim 19 , wherein determining the value comprises dividing the second quantity by the first quantity. | 0.734601 |
8. The method of claim 7, in which the providing step further comprises the step of receiving the telephone call in the language interpretation platform and connecting the telephone call to a language interpreter desired by the subscriber. | 8. The method of claim 7, in which the providing step further comprises the step of receiving the telephone call in the language interpretation platform and connecting the telephone call to a language interpreter desired by the subscriber. 9. The method of claim 8, in which the step of receiving the telephone call in the platform comprises the step of connecting the telephone call to a human operator and transferring the call from the human operator to a language interpreter desired by the subscriber. | 0.816632 |
19. A method utilized during a testimonial proceeding using a remote system, at least one terminal coupled to the remote system, and a transcription system, the method comprising: converting, using the transcription system, representations of spoken words to text in real time, the transcription system being disposed at a first premises; delivering the text in real time to the remote system, the remote system being disposed at a second premises; and delivering, by the remote system, the text in real time to the at least one terminal for display, the at least one terminal being disposed at at least a third premises. | 19. A method utilized during a testimonial proceeding using a remote system, at least one terminal coupled to the remote system, and a transcription system, the method comprising: converting, using the transcription system, representations of spoken words to text in real time, the transcription system being disposed at a first premises; delivering the text in real time to the remote system, the remote system being disposed at a second premises; and delivering, by the remote system, the text in real time to the at least one terminal for display, the at least one terminal being disposed at at least a third premises. 20. The method of claim 19 further comprising: capturing audio signals corresponding to the spoken words; and associating the captured audio signals with the text. | 0.679215 |
1. A method for multilingual administration of enterprise data, the method comprising: retrieving, by at least one device, enterprise data; extracting, by the at least one device, text from the enterprise data for rendering from a digital media file, the extracted text being in a source language; selecting, by the at least one device, a predetermined default target language from among a plurality of target languages based on a data type for the enterprise data; identifying, by the at least one device, that the source language is not the predetermined default target language for rendering the enterprise data; translating, by the at least one device, the extracted text in the source language to translated text in the predetermined default target language; converting, by the at least one device, the translated text to synthesized speech in the predetermined default target language; and recording, by the at least one device, the synthesized speech in the predetermined default target language in a digital media file. | 1. A method for multilingual administration of enterprise data, the method comprising: retrieving, by at least one device, enterprise data; extracting, by the at least one device, text from the enterprise data for rendering from a digital media file, the extracted text being in a source language; selecting, by the at least one device, a predetermined default target language from among a plurality of target languages based on a data type for the enterprise data; identifying, by the at least one device, that the source language is not the predetermined default target language for rendering the enterprise data; translating, by the at least one device, the extracted text in the source language to translated text in the predetermined default target language; converting, by the at least one device, the translated text to synthesized speech in the predetermined default target language; and recording, by the at least one device, the synthesized speech in the predetermined default target language in a digital media file. 5. The method of claim 1 further comprising receiving from the user a selection of the predetermined default target language including receiving through a GUI selection screen a selection of an identification of one of a plurality of available predetermined default target languages. | 0.904313 |
16. The non-transitory computer-readable storage medium of claim 10 , the operations further comprising: identifying a location in the second version of the electronic document corresponding to a location of the portion of the document that is in the image; and providing data that cause presentation of a portion of the second version of the electronic document that corresponds to the identified location. | 16. The non-transitory computer-readable storage medium of claim 10 , the operations further comprising: identifying a location in the second version of the electronic document corresponding to a location of the portion of the document that is in the image; and providing data that cause presentation of a portion of the second version of the electronic document that corresponds to the identified location. 17. The non-transitory computer-readable storage medium of claim 16 , the operations further comprising: receiving an image of a second portion of the document; identifying a second location in the second version of the electronic document corresponding to a location of the second portion of the document; and providing data that cause presentation of a second portion of the second version of the electronic document that corresponds to the second location. | 0.782403 |
1. An apparatus, comprising: a processor circuit; and an application program operative on the processor circuit to manage a collaborative document having a presentation surface with multiple constructs, the application program comprising: a document render component operative to render a first document instance of the collaborative document; a document share component operative to receive a document update list comprising a set of change records for a second document instance of the collaborative document, each change record comprising information for a modification made to a construct of the second document instance, determine whether a time stamp of a change record for the first document instance of the collaborative document and a time stamp of a change record for the second document instance of the collaborative document are both within a synchronization interval when the change records have matching constructs, annotate the change records as conflict records, and modify properties of one or more constructs for the first document instance based on the change records to form a merged document instance of the collaborative document; and an undo manager component operative to manage a local undo stack for the first document instance, the local undo stack comprising a set of undo records each storing information to undo a modification made to a construct of the first document instance, compare the set of undo records and the set of change records, and determine whether to preserve one or more of the undo records of the local undo stack after formation of the merged document instance based on one or more of the change records. | 1. An apparatus, comprising: a processor circuit; and an application program operative on the processor circuit to manage a collaborative document having a presentation surface with multiple constructs, the application program comprising: a document render component operative to render a first document instance of the collaborative document; a document share component operative to receive a document update list comprising a set of change records for a second document instance of the collaborative document, each change record comprising information for a modification made to a construct of the second document instance, determine whether a time stamp of a change record for the first document instance of the collaborative document and a time stamp of a change record for the second document instance of the collaborative document are both within a synchronization interval when the change records have matching constructs, annotate the change records as conflict records, and modify properties of one or more constructs for the first document instance based on the change records to form a merged document instance of the collaborative document; and an undo manager component operative to manage a local undo stack for the first document instance, the local undo stack comprising a set of undo records each storing information to undo a modification made to a construct of the first document instance, compare the set of undo records and the set of change records, and determine whether to preserve one or more of the undo records of the local undo stack after formation of the merged document instance based on one or more of the change records. 2. The apparatus of claim 1 , comprising an undo record storing a time stamp indicating a date and a time when a modification was made to a construct of the first document instance of the document. | 0.560729 |
9. The method according to claim 1 , further comprising transforming one or more of the text documents to an image document. | 9. The method according to claim 1 , further comprising transforming one or more of the text documents to an image document. 11. The method according to claim 9 , further comprising transforming the image document to a paper document. | 0.942408 |
31. A character processing method applicable to an apparatus which stores parameters to generate a plurality of modified font patterns for all character patterns of a single font, said method comprising the steps of: designating a desired one or more of a plurality of items of modification information for each graphic pattern in order to generate a plurality of graphic patterns, the parameters being based on the designated one or more items of modification information; generating a request for display; displaying a plurality of graphic patterns corresponding to a plurality of modified font patterns each corresponding to the same character of the single font on the basis of the parameters stored in the apparatus in response to said request generating step, wherein the one character pattern of the single font is predetermined; selecting one of the plurality of graphic patterns that correspond to the plurality of modified font patterns for the one character pattern displayed in said displaying step; and controlling said display step such that the one graphic pattern corresponding to the modified font pattern selected in said selecting step is displayed in said displaying step distinguishably from other graphic patterns corresponding to the other modified font patterns. | 31. A character processing method applicable to an apparatus which stores parameters to generate a plurality of modified font patterns for all character patterns of a single font, said method comprising the steps of: designating a desired one or more of a plurality of items of modification information for each graphic pattern in order to generate a plurality of graphic patterns, the parameters being based on the designated one or more items of modification information; generating a request for display; displaying a plurality of graphic patterns corresponding to a plurality of modified font patterns each corresponding to the same character of the single font on the basis of the parameters stored in the apparatus in response to said request generating step, wherein the one character pattern of the single font is predetermined; selecting one of the plurality of graphic patterns that correspond to the plurality of modified font patterns for the one character pattern displayed in said displaying step; and controlling said display step such that the one graphic pattern corresponding to the modified font pattern selected in said selecting step is displayed in said displaying step distinguishably from other graphic patterns corresponding to the other modified font patterns. 34. A character processing method according to claim 31, wherein the parameters previously selected are maintained. | 0.612515 |
1. A method for generating documentation, comprising: receiving at a document generation system data representative of required data from a remote system, the remote system configured to selectively operate in accordance with at least an automatic mode of document selection and a manual mode of document selection, the required data in an extensible markup language (XML) format and received at the document generation system via a data network, the data including an indication of a document generation mode comprising one of the automatic mode of document selection, where the document generation system identifies at least one document to be populated with the required data, and the manual mode of document selection, where the data received from the remote system identifies the at least one document to be populated with the required data; invoking the one of the automatic mode and the manual mode of document selection in response to the received data indicative of the document generation mode; selecting from a document repository and assembling the at least one document to be populated with the required data; validating the required data in relation to a set of requirements associated with the at least one document; merging the required data with the at least one document; and streaming the at least one document via the data network in a presentation format to the remote system for at least one of presentation and printing. | 1. A method for generating documentation, comprising: receiving at a document generation system data representative of required data from a remote system, the remote system configured to selectively operate in accordance with at least an automatic mode of document selection and a manual mode of document selection, the required data in an extensible markup language (XML) format and received at the document generation system via a data network, the data including an indication of a document generation mode comprising one of the automatic mode of document selection, where the document generation system identifies at least one document to be populated with the required data, and the manual mode of document selection, where the data received from the remote system identifies the at least one document to be populated with the required data; invoking the one of the automatic mode and the manual mode of document selection in response to the received data indicative of the document generation mode; selecting from a document repository and assembling the at least one document to be populated with the required data; validating the required data in relation to a set of requirements associated with the at least one document; merging the required data with the at least one document; and streaming the at least one document via the data network in a presentation format to the remote system for at least one of presentation and printing. 2. The method of claim 1 , wherein the remote system comprises at least one of a dealer management system, a credit aggregator partner, and a financial services dealer. | 0.566818 |
1. A computer-implemented method comprising: receiving a source code at a compiler on a machine, the source code comprising a new keyword to a scripting language of the compiler; processing, using a processor of the machine, the source code with an extension compiler module configured to support the new keyword; the extension compiler module is further configured to support various contexts by specifying snippet metadata describing the context in which the language is used and define different snippet signatures from different runtime contexts; and generating an executable machine code based on a process of the extension compiler module and the compiler. | 1. A computer-implemented method comprising: receiving a source code at a compiler on a machine, the source code comprising a new keyword to a scripting language of the compiler; processing, using a processor of the machine, the source code with an extension compiler module configured to support the new keyword; the extension compiler module is further configured to support various contexts by specifying snippet metadata describing the context in which the language is used and define different snippet signatures from different runtime contexts; and generating an executable machine code based on a process of the extension compiler module and the compiler. 2. The computer-implemented method of claim 1 , wherein the compiler is configured to: analyze a syntax of the source code; analyze a semantic of the source code; and generate the executable machine code based on the syntax and semantic of the source code. | 0.558 |
7. The system of claim 6 , wherein pre-processing the plurality of labeled sentences comprises handling negation words in each of the plurality of labeled sentences. | 7. The system of claim 6 , wherein pre-processing the plurality of labeled sentences comprises handling negation words in each of the plurality of labeled sentences. 9. The system of claim 7 , wherein handling the negation words comprises applying a parsing algorithm to join the negation words with those words of the sentence to which the negation applies. | 0.938339 |
24. The computer readable storage medium of claim 21 , wherein the step of processing the first one or more blocks of unstructured text includes the step of identifying first unstructured textual data in a form of a name followed by a corresponding value. | 24. The computer readable storage medium of claim 21 , wherein the step of processing the first one or more blocks of unstructured text includes the step of identifying first unstructured textual data in a form of a name followed by a corresponding value. 25. The computer readable storage medium of claim 24 , wherein the step of identifying the first unstructured textual data in a form of a name followed by a corresponding value includes: identifying in the first test responses a line including a pattern of the name followed by the corresponding value; and generating a query identified by the name, the corresponding value being extracted by the query. | 0.852174 |
22. A method for searching for media items using a voice-based digital assistant, comprising: at an electronic device with a processor and memory storing instructions for execution by the processor: providing a plurality of media items wherein at least some of the media items are each associated with a respective tag comprising at least one of a time tag, a date tag, or a geo-code tag; providing a natural language text string corresponding to a search query for one or more media items, wherein the search query includes one or more query terms; identifying, based on the search query, a first media item of the plurality of media items, wherein the media item is associated with user-generated information and wherein the user-generated information matches a query term of the one or more query terms; comparing the respective tags of the identified first media item to the respective tags of one or more other media items of the plurality of media items to identify a second media item, wherein the respective tags of the identified first media item are not generated based on the search query; and facilitating a presentation of the first media item and the second media item to a user. | 22. A method for searching for media items using a voice-based digital assistant, comprising: at an electronic device with a processor and memory storing instructions for execution by the processor: providing a plurality of media items wherein at least some of the media items are each associated with a respective tag comprising at least one of a time tag, a date tag, or a geo-code tag; providing a natural language text string corresponding to a search query for one or more media items, wherein the search query includes one or more query terms; identifying, based on the search query, a first media item of the plurality of media items, wherein the media item is associated with user-generated information and wherein the user-generated information matches a query term of the one or more query terms; comparing the respective tags of the identified first media item to the respective tags of one or more other media items of the plurality of media items to identify a second media item, wherein the respective tags of the identified first media item are not generated based on the search query; and facilitating a presentation of the first media item and the second media item to a user. 33. The method of claim 22 , wherein at least one of the plurality of media items is a video. | 0.580043 |
10. The method of claim 7 , wherein the text flow specifies at least one of a character progression and a line progression of the text data within the region. | 10. The method of claim 7 , wherein the text flow specifies at least one of a character progression and a line progression of the text data within the region. 12. The method of claim 10 , wherein a direction of the line progression is one of a top-to-bottom line progression and a bottom-to-top line progression. | 0.943005 |
12. A system comprising: a processor; and a memory containing a program configured for execution on the processor, the program comprising: a record profile configuration user interface; a set of record profiles generated by said record profile configuration user interface; a mapping definition configuration user interface; a set of mapping definitions generated by said mapping definition configuration user interface definitions, wherein each mapping definition in the set of mapping definitions includes an ordered set of rules to select a particular one of said plurality of record profiles, each mapping definition being associated with a respective one of a plurality of document classes, wherein each rule in said ordered set of rules corresponds to a respective one of said plurality of record profiles and comprises a combination of logical operations that are applied to specific property values of a new document that has been checked into an object store, wherein each mapping definition further includes a match rule at the end of said ordered set of rules that is a default record profile mapping rule corresponding to a default record profile in said plurality of record profiles, and wherein said match rule is satisfied in the event that no match occurs for any of the other rules in said set of ordered rules; a content engine event handler configured to transmit one or more subscription requests for check-in events for said plurality of document classes to an object store event manager, wherein said object store event manager transmits a check-in event whenever a document belonging to one of said plurality of document classes is checked into said object store and further configured to receive a check-in event specifying that a new document from one of said plurality of document classes has been checked into said object store, and further to automatically apply at least one of said mapping definitions to said new document to select one of said record profiles to be associated with said new document; and a new record declaration unit for using said selected record profile to automatically declarate a new record for said new document without any user interaction. | 12. A system comprising: a processor; and a memory containing a program configured for execution on the processor, the program comprising: a record profile configuration user interface; a set of record profiles generated by said record profile configuration user interface; a mapping definition configuration user interface; a set of mapping definitions generated by said mapping definition configuration user interface definitions, wherein each mapping definition in the set of mapping definitions includes an ordered set of rules to select a particular one of said plurality of record profiles, each mapping definition being associated with a respective one of a plurality of document classes, wherein each rule in said ordered set of rules corresponds to a respective one of said plurality of record profiles and comprises a combination of logical operations that are applied to specific property values of a new document that has been checked into an object store, wherein each mapping definition further includes a match rule at the end of said ordered set of rules that is a default record profile mapping rule corresponding to a default record profile in said plurality of record profiles, and wherein said match rule is satisfied in the event that no match occurs for any of the other rules in said set of ordered rules; a content engine event handler configured to transmit one or more subscription requests for check-in events for said plurality of document classes to an object store event manager, wherein said object store event manager transmits a check-in event whenever a document belonging to one of said plurality of document classes is checked into said object store and further configured to receive a check-in event specifying that a new document from one of said plurality of document classes has been checked into said object store, and further to automatically apply at least one of said mapping definitions to said new document to select one of said record profiles to be associated with said new document; and a new record declaration unit for using said selected record profile to automatically declarate a new record for said new document without any user interaction. 14. The system according to claim 12 further comprising a Boolean flag for the automatic transfer of document property values to matching record property values. | 0.535566 |
2. The method of claim 1 , wherein the collection of documents is generated by a query request. | 2. The method of claim 1 , wherein the collection of documents is generated by a query request. 3. The method of claim 2 , wherein the contents of the documents are represented by respective titles and respective document texts. | 0.940252 |
74. The system of claim 73 , wherein the feedback comprises any of visual feedback and audio feedback. | 74. The system of claim 73 , wherein the feedback comprises any of visual feedback and audio feedback. 75. The system of claim 74 , wherein the visual feedback comprises any of an ink trail corresponding to the determined device path, a font change, a color change, a reverse video color, an alternate background color, an underline, bold face text, italic text, and a text outline. | 0.911333 |
19. The method of claim 13 wherein the hierarchical data structure is a binary trie. | 19. The method of claim 13 wherein the hierarchical data structure is a binary trie. 20. The method of claim 19 wherein the hierarchical data structure provides a minimal perfect hash function. | 0.975964 |
1. A method comprising: creating, by one or more processors, news content from a plurality of news items; receiving, by the one or more processors, a request to remove a news item, of the plurality of news items, from the news content; removing, by the one or more processors, the news item and one or more similar news items, of the plurality of news items, with content similar to content of the news item from the news content; identifying, by the one or more processors, replacement news items to replace the news item and the one or more similar news items; creating, by one or more processors, updated news content by replacing the news item and the one or more similar news items with the replacement news items; and providing, by the one or more processors, the updated news content. | 1. A method comprising: creating, by one or more processors, news content from a plurality of news items; receiving, by the one or more processors, a request to remove a news item, of the plurality of news items, from the news content; removing, by the one or more processors, the news item and one or more similar news items, of the plurality of news items, with content similar to content of the news item from the news content; identifying, by the one or more processors, replacement news items to replace the news item and the one or more similar news items; creating, by one or more processors, updated news content by replacing the news item and the one or more similar news items with the replacement news items; and providing, by the one or more processors, the updated news content. 6. The method of claim 1 , further comprising: identifying previously accessed news content of the updated news content; and removing the previously accessed news content from the updated news content. | 0.652485 |
2. The method of claim 1 , further comprising: in response to receiving the first client request, generating a second plurality of requests, each of which requests a different set of data from a second source that is different than the first source; sending the second plurality of requests to the second source. | 2. The method of claim 1 , further comprising: in response to receiving the first client request, generating a second plurality of requests, each of which requests a different set of data from a second source that is different than the first source; sending the second plurality of requests to the second source. 3. The method of claim 2 , wherein the different set of data from the second source is the same as the different set of data from the first source. | 0.928799 |
1. A computer-implemented method of grouping search results using information representations, the method comprising: receiving an input for selecting an object having a first object type; displaying, by a server computer, on a graphical user interface, at least one tile that graphically represents at least one user associated with the selected object; determining a chronological timeline that represents a plurality of actions performed by the at least one user, wherein the plurality of actions performed by at least one user have a plurality of chronological positions in the chronological timeline; inferring one or more relationships between the selected object and one or more other objects associated with the at least one user from the plurality of actions represented in the chronological timeline, wherein inferring the one or more relationships includes: identifying one or more of the plurality of actions that are related to the selected object from the plurality of chronological positions that the plurality of actions have in the chronological timeline, wherein the at least one user performed the identified one or more actions on the one or more other objects, and wherein the one or more other objects have a second object type different from the first object type; and determining that the one or more other objects are related to the selected object from a strength of the one or more inferred relationships, wherein the strength of the one or more inferred relationships is derived from the chronological positions that the identified one or more actions have in the chronological timeline, generating one or more additional tiles that graphically represent the one or more other objects related to the selected object and performed by the at least one user in response to a selection of the at least one tile that graphically represents the at least one user; and simultaneously displaying, on the graphical user interface, the one or more additional tiles that graphically represent the one or more other objects related to the selected object and performed by the at least one user, wherein the graphical user interface further organizes the at least one tile and the one or more additional tiles based on the first object type for the selected object and the second object type for the one or more other objects. | 1. A computer-implemented method of grouping search results using information representations, the method comprising: receiving an input for selecting an object having a first object type; displaying, by a server computer, on a graphical user interface, at least one tile that graphically represents at least one user associated with the selected object; determining a chronological timeline that represents a plurality of actions performed by the at least one user, wherein the plurality of actions performed by at least one user have a plurality of chronological positions in the chronological timeline; inferring one or more relationships between the selected object and one or more other objects associated with the at least one user from the plurality of actions represented in the chronological timeline, wherein inferring the one or more relationships includes: identifying one or more of the plurality of actions that are related to the selected object from the plurality of chronological positions that the plurality of actions have in the chronological timeline, wherein the at least one user performed the identified one or more actions on the one or more other objects, and wherein the one or more other objects have a second object type different from the first object type; and determining that the one or more other objects are related to the selected object from a strength of the one or more inferred relationships, wherein the strength of the one or more inferred relationships is derived from the chronological positions that the identified one or more actions have in the chronological timeline, generating one or more additional tiles that graphically represent the one or more other objects related to the selected object and performed by the at least one user in response to a selection of the at least one tile that graphically represents the at least one user; and simultaneously displaying, on the graphical user interface, the one or more additional tiles that graphically represent the one or more other objects related to the selected object and performed by the at least one user, wherein the graphical user interface further organizes the at least one tile and the one or more additional tiles based on the first object type for the selected object and the second object type for the one or more other objects. 8. The method of claim 1 , wherein the strength of the one or more inferred relationships are further derived from content of the selected object, content of the one or more other objects, or a combination of both. | 0.617198 |
6. The system of claim 1 , wherein the one or more processors are further programmed by the executable instructions to at least: obtain hint data indicating a likely subject matter with which the text is associated, wherein the hint data is based on at least one of a previous user input and a previous response; and adjust at least one of the first score and the second score based at least partly on the hint data. | 6. The system of claim 1 , wherein the one or more processors are further programmed by the executable instructions to at least: obtain hint data indicating a likely subject matter with which the text is associated, wherein the hint data is based on at least one of a previous user input and a previous response; and adjust at least one of the first score and the second score based at least partly on the hint data. 7. The system of claim 6 , wherein the executable instructions to adjust at least one of the first score and the second score based at least partly on the hint data comprise instructions to reduce the second score based at least partly on the hint data indicating that the text is more likely associated with the first subject matter than the second subject matter. | 0.833598 |
11. A system for accessing an out-space user interface for a program, comprising: a processor; a display; and a memory having computer-executable instructions stored thereon, wherein the computer-executable instructions are configured to: display a document editor including an in-space actuator and an out-space actuator; in response to receiving a selection of the in-space actuator, display the in-space user interface comprising an in-space user interface area comprising in-space user interface elements and a document display area to display a document, wherein the in-space user interface area comprises a ribbon comprising ribbon tabs and authoring features for authoring the content of the document; and in response to receiving a selection of the out-space actuator, remove at least a portion of the in-space user interface elements displayed in the in-space user interface area, and display the out-space user interface within the document display area, the out-space user interface comprising out-space user interface elements that when selected do not affect the content of the document, and wherein the out-space user interface elements include non-authoring features associated with the document in the document display area. | 11. A system for accessing an out-space user interface for a program, comprising: a processor; a display; and a memory having computer-executable instructions stored thereon, wherein the computer-executable instructions are configured to: display a document editor including an in-space actuator and an out-space actuator; in response to receiving a selection of the in-space actuator, display the in-space user interface comprising an in-space user interface area comprising in-space user interface elements and a document display area to display a document, wherein the in-space user interface area comprises a ribbon comprising ribbon tabs and authoring features for authoring the content of the document; and in response to receiving a selection of the out-space actuator, remove at least a portion of the in-space user interface elements displayed in the in-space user interface area, and display the out-space user interface within the document display area, the out-space user interface comprising out-space user interface elements that when selected do not affect the content of the document, and wherein the out-space user interface elements include non-authoring features associated with the document in the document display area. 19. The system of claim 11 , wherein the out-space actuator is actuated in response to a single actuation. | 0.621999 |
8. The method as recited in claim 1 , wherein the determining comprises: extracting at least one content characteristic from a response received from the URL; analyzing the at least one content characteristic for mobile-friendliness; and determining the mobile-friendliness indication based on the analyzing. | 8. The method as recited in claim 1 , wherein the determining comprises: extracting at least one content characteristic from a response received from the URL; analyzing the at least one content characteristic for mobile-friendliness; and determining the mobile-friendliness indication based on the analyzing. 9. The method as recited in claim 8 , wherein the analyzing comprises at least one of: checking for a script or a frame in the response; detecting a size of an image in the response; or detecting a total memory size of the response. | 0.87592 |
18. A system for searching optical character recognition results of image text documents comprising: an image text transformer linguistically analyzing the optical character recognition results within a context of multiple lexicons to form edited text results, and creating reflection files corresponding to the image text documents from the edited text results; a reflection repository storing the reflection files therein; a search engine searching the reflection files; and a user device displaying a first reflection file from the reflection files or a first image text document from the image text documents in response to searching. | 18. A system for searching optical character recognition results of image text documents comprising: an image text transformer linguistically analyzing the optical character recognition results within a context of multiple lexicons to form edited text results, and creating reflection files corresponding to the image text documents from the edited text results; a reflection repository storing the reflection files therein; a search engine searching the reflection files; and a user device displaying a first reflection file from the reflection files or a first image text document from the image text documents in response to searching. 22. A system as recited in claim 18 wherein the content repository stores metadata associated with the image text documents. | 0.549861 |
19. In the system of claim 18, further comprising processor means connected to said input synchronizer means and responsive to said sequence of corresponding phonemes for breaking down the sequence of corresponding phonemes into syllabits, each syllabit comprising a group of classes of sounds. | 19. In the system of claim 18, further comprising processor means connected to said input synchronizer means and responsive to said sequence of corresponding phonemes for breaking down the sequence of corresponding phonemes into syllabits, each syllabit comprising a group of classes of sounds. 20. In the system of claim 19, wherein said processing means groups the syllabits into syllabit groups, each syllabit group defining corresponding possible words, and wherein said processor means provides, for each of said possible words corresponding to each syllabit group, a respective skeletal sequence of phonemes comprising a corresponding grouping of phonemes. | 0.865992 |
1. A computer-implemented method for representing an ontological information system for illness based on Chinese Traditional Medicine, the method comprising: generating, through a computer, ontological information comprising symptoms and associated illnesses in Chinese Traditional Medicine in annotated form, wherein the symptoms are categorized as major, minor, tongue surface and pulse according to Chinese Traditional Medicine; converting, via a semantic net of the computer, the ontological information into logic representations; providing a graphic system of queries regarding symptoms for receiving user input into the computer based on the ontological information; receiving user input symptoms in response to the queries; parsing illnesses in the ontological information associated with the user input symptoms; matching the user input symptoms with expected symptoms of parsed illnesses; assigning a weighted value to a user input symptom matched with an expected symptom of a parsed illness based on the symptom category, wherein if a matched user input symptom is of greater importance to the parsed illness, the matched user input symptom is assigned a higher weighted value, and if a matched user input symptom is of less importance to the parsed illness, the matched user input symptom is assigned a lower weighted value; calculating a relevance index by comparing the user input symptoms with the expected symptoms of parsed illnesses, each parsed illness that has a user input symptom matching an expected symptom of the respective parsed illness having an entry in the relevance index, each entry in the relevance index comprising a parsed illness and a numerical value being the number of user input symptoms that match the expected symptoms of the respective parsed illness; calculating a frequency index to evaluate the parsed illness and using the frequency index in calculating a modified relevance index, wherein the frequency index is calculated based on: determining a total number of user input symptoms that match the expected symptoms of a respective parsed illness; separating each user input symptom that matches an expected symptom of a respective parsed illness into a sub-category; assigning a weighted value to each sub-category; for each respective sub-category of a parsed illness, calculate a quotient by dividing the total number of matched user input symptoms with the number of user input symptoms in the sub-category, then calculate a product by multiplying the quotient by the respective weighted value for the sub-category, and then calculate a sum for each parsed illness by adding together each product for each sub-category of the parsed illness; providing a graphic index comprising a ranked column of parsed illnesses and an adjacent column comprising a relevance index value for each respective parsed illness, the ranked column of parsed illnesses being in ascending order of a parsed illness having a highest number of user input symptoms matching the expected symptoms of the respective parsed illness to a parsed illness having a lowest number of user input symptoms matching the expected symptoms of the respective parsed illness, the adjacent column providing the number of matched user input symptoms with the expected symptoms of each respective parsed illness; when the frequency index for the parsed illness falls below a threshold value, and when one or more unmatched user input symptom is in a major symptom category, adding to the ontological information a new disease descriptor having the matched user input symptoms and the one or more unmatched user input symptom in the major symptom category; and communicating to the user, illnesses in Chinese Traditional Medicine derived from the semantic net associated with the user input symptoms, wherein the semantic net is a document object model, and wherein the expected symptom is selected from: chills and fever; sweat; cough; sputum; pain; sleep disturbance; vomiting; vaginal discharge; and alterations in complexion, nose, lips, throat, pharynx or tongue. | 1. A computer-implemented method for representing an ontological information system for illness based on Chinese Traditional Medicine, the method comprising: generating, through a computer, ontological information comprising symptoms and associated illnesses in Chinese Traditional Medicine in annotated form, wherein the symptoms are categorized as major, minor, tongue surface and pulse according to Chinese Traditional Medicine; converting, via a semantic net of the computer, the ontological information into logic representations; providing a graphic system of queries regarding symptoms for receiving user input into the computer based on the ontological information; receiving user input symptoms in response to the queries; parsing illnesses in the ontological information associated with the user input symptoms; matching the user input symptoms with expected symptoms of parsed illnesses; assigning a weighted value to a user input symptom matched with an expected symptom of a parsed illness based on the symptom category, wherein if a matched user input symptom is of greater importance to the parsed illness, the matched user input symptom is assigned a higher weighted value, and if a matched user input symptom is of less importance to the parsed illness, the matched user input symptom is assigned a lower weighted value; calculating a relevance index by comparing the user input symptoms with the expected symptoms of parsed illnesses, each parsed illness that has a user input symptom matching an expected symptom of the respective parsed illness having an entry in the relevance index, each entry in the relevance index comprising a parsed illness and a numerical value being the number of user input symptoms that match the expected symptoms of the respective parsed illness; calculating a frequency index to evaluate the parsed illness and using the frequency index in calculating a modified relevance index, wherein the frequency index is calculated based on: determining a total number of user input symptoms that match the expected symptoms of a respective parsed illness; separating each user input symptom that matches an expected symptom of a respective parsed illness into a sub-category; assigning a weighted value to each sub-category; for each respective sub-category of a parsed illness, calculate a quotient by dividing the total number of matched user input symptoms with the number of user input symptoms in the sub-category, then calculate a product by multiplying the quotient by the respective weighted value for the sub-category, and then calculate a sum for each parsed illness by adding together each product for each sub-category of the parsed illness; providing a graphic index comprising a ranked column of parsed illnesses and an adjacent column comprising a relevance index value for each respective parsed illness, the ranked column of parsed illnesses being in ascending order of a parsed illness having a highest number of user input symptoms matching the expected symptoms of the respective parsed illness to a parsed illness having a lowest number of user input symptoms matching the expected symptoms of the respective parsed illness, the adjacent column providing the number of matched user input symptoms with the expected symptoms of each respective parsed illness; when the frequency index for the parsed illness falls below a threshold value, and when one or more unmatched user input symptom is in a major symptom category, adding to the ontological information a new disease descriptor having the matched user input symptoms and the one or more unmatched user input symptom in the major symptom category; and communicating to the user, illnesses in Chinese Traditional Medicine derived from the semantic net associated with the user input symptoms, wherein the semantic net is a document object model, and wherein the expected symptom is selected from: chills and fever; sweat; cough; sputum; pain; sleep disturbance; vomiting; vaginal discharge; and alterations in complexion, nose, lips, throat, pharynx or tongue. 3. The method of claim 1 , wherein the ontological information is stored in a memory of the computer. | 0.879147 |
2. The method of claim 1 wherein said text-based message is an e-mail message. | 2. The method of claim 1 wherein said text-based message is an e-mail message. 4. The method of claim 2 wherein said extracting contents of at least two fields comprises extracting contents of a “TO” field of said text-based message. | 0.969856 |
11. A method implemented by a data processing apparatus, comprising: accessing an index of first and second resources, the first resources being resources that are different from the second resources; for each indexed first resource: selecting, from a query log, queries for which search results referencing the first resource were selected at a user device in response to the queries; for each of the queries, accessing data specifying an actual search property ratio for the query, the actual search property ratio being a ratio of a first number of times the query was used to search first resources and a second number of times the query was used to search second resources; and determining, by the data processing apparatus, a resource search property ratio score for the first resource based on the actual search property ratios of each of the queries; identifying websites hosting the first resources, each website hosting one or more of the first resources; and determining, for each of the websites, a website search property ratio based on the actual search property ratios of each of the queries for which search results referencing the first resource hosted on the website were selected; receiving a query for a search of the first resources; selecting at least a proper subset of resources that are determined to be responsive to the query; determining an actual search property ratio of the query that is proportional to a number of times the query was submitted for a search of the second resources to a number of times that the search query was submitted for a search of the first resources; and determining an insertion score based on a first insertion score that is proportional to the actual search property ratio and a first weighting value and a second insertion score from a proper subset of resources that have the highest first search scores for the query and based on the resource search property ratio scores of the proper subset of resources and a second weighting value. | 11. A method implemented by a data processing apparatus, comprising: accessing an index of first and second resources, the first resources being resources that are different from the second resources; for each indexed first resource: selecting, from a query log, queries for which search results referencing the first resource were selected at a user device in response to the queries; for each of the queries, accessing data specifying an actual search property ratio for the query, the actual search property ratio being a ratio of a first number of times the query was used to search first resources and a second number of times the query was used to search second resources; and determining, by the data processing apparatus, a resource search property ratio score for the first resource based on the actual search property ratios of each of the queries; identifying websites hosting the first resources, each website hosting one or more of the first resources; and determining, for each of the websites, a website search property ratio based on the actual search property ratios of each of the queries for which search results referencing the first resource hosted on the website were selected; receiving a query for a search of the first resources; selecting at least a proper subset of resources that are determined to be responsive to the query; determining an actual search property ratio of the query that is proportional to a number of times the query was submitted for a search of the second resources to a number of times that the search query was submitted for a search of the first resources; and determining an insertion score based on a first insertion score that is proportional to the actual search property ratio and a first weighting value and a second insertion score from a proper subset of resources that have the highest first search scores for the query and based on the resource search property ratio scores of the proper subset of resources and a second weighting value. 13. The method of claim 11 , further comprising: receiving a query for a search of the first resources; selecting at least a proper subset of resources that are determined to be responsive to the query; and determining, for the query, an insertion score for the query, the insertion score based on a ratio of a first number of resources in the proper subset of resources having a resource search property ratio meeting a resource search property ratio threshold to a second number that is equal to the cardinality of the proper subset of resources. | 0.668701 |
1. A network device configured to send and receive data over a network, the network device comprising: at least one non-transitory storage medium comprising at least one set of instructions for feature expansions of online advertisements; at least one processor in communication with the at least one non-transitory storage medium and configured to execute the at least one set of instructions to: receive an advertisement with Ad keywords associated with the advertisement; segment content of the advertisement into a plurality of phrases; perform a semantic analysis to the plurality of phrases; select top-ranked phrases from the plurality of phrases based on the semantic analysis to form a reduced subset of phrases generate a query list having a plurality of queries by combining each phrase in the reduced subset of phrases that has less than a defined number of words with another independent phrase in the reduced subset of phrases to create queries comprising two or more words; for each query within the query list, perform an internet web search to identify a set of descriptions, each description describing a search result from the internet web search; select a second set of phrases denoted as a query expansion feature set for each query based on an analysis of the set of descriptions; rank the second set of phrases; generate an expanded Ad index, wherein to generate the expanded Ad index the at least one processor is configured to: select from the ranked second set of phrases a subset of phrases as an ad expanded feature set; and combine the ad expanded feature set with the Ad keywords associated with the advertisement; and when in receipt of a request to provide to a client device a second content for display, select an advertisement from a plurality of advertisements based on the expanded Ad index. | 1. A network device configured to send and receive data over a network, the network device comprising: at least one non-transitory storage medium comprising at least one set of instructions for feature expansions of online advertisements; at least one processor in communication with the at least one non-transitory storage medium and configured to execute the at least one set of instructions to: receive an advertisement with Ad keywords associated with the advertisement; segment content of the advertisement into a plurality of phrases; perform a semantic analysis to the plurality of phrases; select top-ranked phrases from the plurality of phrases based on the semantic analysis to form a reduced subset of phrases generate a query list having a plurality of queries by combining each phrase in the reduced subset of phrases that has less than a defined number of words with another independent phrase in the reduced subset of phrases to create queries comprising two or more words; for each query within the query list, perform an internet web search to identify a set of descriptions, each description describing a search result from the internet web search; select a second set of phrases denoted as a query expansion feature set for each query based on an analysis of the set of descriptions; rank the second set of phrases; generate an expanded Ad index, wherein to generate the expanded Ad index the at least one processor is configured to: select from the ranked second set of phrases a subset of phrases as an ad expanded feature set; and combine the ad expanded feature set with the Ad keywords associated with the advertisement; and when in receipt of a request to provide to a client device a second content for display, select an advertisement from a plurality of advertisements based on the expanded Ad index. 2. The network device of claim 1 , wherein to conduct the semantic analysis, the at least one processor is further configured to: group related of words from the content of the advertisement to generate a phrase from the content of the advertisement; determine a pointwise mutual information (PMI) value for each generated phrase with each Ad keyword; rank in order the determined PMI values based on a Term Frequency-Inverse Document Frequency (TF-IDF) score for each generated phrase; and select from the rank ordering a subset of phrases as the reduced subset of phrases for the advertisement. | 0.5 |
6. A method comprising: receiving a request from a client device for a preview of a native document, the preview representing the native document in a file format other than the file format of the native document; inserting, by a document mapping module in the native document prior to rendering a preview, a set of unique links comprising a uniform resource locator (URL) and each unique link associated with a different word in the native document, the native object comprising a renderable portion of the native document; rendering, by a document rendering module, the native document into a preview of the native document and thereby generating a bounding area for each of the unique links in the set of unique links, the bounding area mapping a page and pixel location on the preview to the native object associated with the unique link; and providing the preview to the client device for display. | 6. A method comprising: receiving a request from a client device for a preview of a native document, the preview representing the native document in a file format other than the file format of the native document; inserting, by a document mapping module in the native document prior to rendering a preview, a set of unique links comprising a uniform resource locator (URL) and each unique link associated with a different word in the native document, the native object comprising a renderable portion of the native document; rendering, by a document rendering module, the native document into a preview of the native document and thereby generating a bounding area for each of the unique links in the set of unique links, the bounding area mapping a page and pixel location on the preview to the native object associated with the unique link; and providing the preview to the client device for display. 8. The method of claim 6 , further comprising: receiving a request to add a comment to the preview indicating a selected portion of the preview for the comment; identifying a location on the preview of the selected portion of the preview; identifying a set of native objects corresponding to the location by matching the location to bounding areas for one or more unique links associated with the identified set of native objects; and inserting the comment in the native document at the location of the identified set of native objects. | 0.610313 |
20. A method, performed by one or more server devices, the method comprising: storing, in a memory of the one or more server devices, a plurality of query-document associations, each query-document association including a one-to-one pairing of an issued search query and a stored search document that was retrieved based on the issued search query; receiving, by one or more processors of the one or more server devices, a search query from a client device; identifying, by one or more processors of the one or more server devices, a set of search result documents using the received search query; identifying, by one or more processors of the one or more server devices, search result documents in the identified set of search result documents that match stored search documents; forming, by one or more processors of the one or more server devices, a plurality of clusters of the search documents, of the stored plurality of query-document associations, that match the search result documents; selecting, by one or more processors of the one or more server devices, at least one of the plurality of clusters; computing, by one or more processors of the one or more server devices, a centroid for each of the selected at least one of the plurality of clusters; computing, by one or more processors of the one or more server devices, a score for each unique issued search query associated with a document in the selected at least one of a plurality of clusters based on the computed centroid; identifying, by one or more processors of the one or more server devices, for a stored search document of the selected at least one of the plurality of clusters, a query-document association in the plurality of query-document associations based on the computed scores; formulating, by one or more processors of the one or more server devices, a search query refinement suggestion for the received search query based on an issued search query of the identified query-document association; and sorting, by one or more processors of the one or more sever devices, the formulated search query refinement suggestion among a group of search query refinement suggestions. | 20. A method, performed by one or more server devices, the method comprising: storing, in a memory of the one or more server devices, a plurality of query-document associations, each query-document association including a one-to-one pairing of an issued search query and a stored search document that was retrieved based on the issued search query; receiving, by one or more processors of the one or more server devices, a search query from a client device; identifying, by one or more processors of the one or more server devices, a set of search result documents using the received search query; identifying, by one or more processors of the one or more server devices, search result documents in the identified set of search result documents that match stored search documents; forming, by one or more processors of the one or more server devices, a plurality of clusters of the search documents, of the stored plurality of query-document associations, that match the search result documents; selecting, by one or more processors of the one or more server devices, at least one of the plurality of clusters; computing, by one or more processors of the one or more server devices, a centroid for each of the selected at least one of the plurality of clusters; computing, by one or more processors of the one or more server devices, a score for each unique issued search query associated with a document in the selected at least one of a plurality of clusters based on the computed centroid; identifying, by one or more processors of the one or more server devices, for a stored search document of the selected at least one of the plurality of clusters, a query-document association in the plurality of query-document associations based on the computed scores; formulating, by one or more processors of the one or more server devices, a search query refinement suggestion for the received search query based on an issued search query of the identified query-document association; and sorting, by one or more processors of the one or more sever devices, the formulated search query refinement suggestion among a group of search query refinement suggestions. 21. The method of claim 20 , further comprising: assigning weights to the stored query-document associations based on relevancies of the search documents to the issued search queries in the query-document associations; and storing the assigned weights. | 0.533997 |
5. A system according to claim 3 , further comprising: a rotation module to rotate the unplaced spine group around the center ring when the unplaced spine group and the most similar placed unique spine overlap. | 5. A system according to claim 3 , further comprising: a rotation module to rotate the unplaced spine group around the center ring when the unplaced spine group and the most similar placed unique spine overlap. 6. A system according to claim 5 , wherein the unplaced spine group is rotated in a direction comprising at least one of a clockwise and a counter-clockwise direction. | 0.889831 |
6. The method of claim 5 , further comprising the set of installation tools issuing a third prompt to provide at least one answer to the at least one question. | 6. The method of claim 5 , further comprising the set of installation tools issuing a third prompt to provide at least one answer to the at least one question. 7. The method of claim 6 , wherein the third prompt comprises a prompt to provide answers to questions other than the at least one question from the first set of questions based on the at least one answer. | 0.950193 |
18. The method of claim 14 , wherein the editable electronic document is an editable electronic form. | 18. The method of claim 14 , wherein the editable electronic document is an editable electronic form. 20. The method of claim 18 , further comprising, if the viewing capabilities do not permit two or more of the hierarchical viewing levels to be presented at once or the request is received, building different renderable view information by which a different computing device with different viewing capabilities that permit two or more of the hierarchical viewing levels to be presented at once is enabled to continue editing the edited data instance. | 0.92096 |
1. A method of graphically displaying relationships between content of a computer file system on a graphical user interface, comprising: gathering file system metadata using a processor, said file system metadata being descriptive of the computer file system, the computer file system comprising a plurality of files; gathering a set of file metadata using said processor, said set of file metadata comprising a description of each of said plurality of files; receiving a file selection from a user; determining a user context using said processor, wherein said user context comprises said file selected, a user profile, an application being used by said user, and file metadata of said file selected by said user, said file metadata comprising a description of a current task said user is performing; clustering the plurality of files into file clusters using the file system metadata, the set of file metadata, and the user context; mapping the set of file clusters with said processor onto a visualization model; graphically displaying the contents of the computer file system on the graphical user interface using said visualization model, wherein said graphical display depicts a relationship between contents of the computer file system at least partially based upon said user context; wherein the computer file system has a programming interface adapted for displaying file system information on the graphical user interface, and wherein the visualization model is graphically displayed on the graphical user interface by overriding the programming interface; and wherein the visualization model is at least one of a network visualization model, an orbital visualization model, and a mind map. | 1. A method of graphically displaying relationships between content of a computer file system on a graphical user interface, comprising: gathering file system metadata using a processor, said file system metadata being descriptive of the computer file system, the computer file system comprising a plurality of files; gathering a set of file metadata using said processor, said set of file metadata comprising a description of each of said plurality of files; receiving a file selection from a user; determining a user context using said processor, wherein said user context comprises said file selected, a user profile, an application being used by said user, and file metadata of said file selected by said user, said file metadata comprising a description of a current task said user is performing; clustering the plurality of files into file clusters using the file system metadata, the set of file metadata, and the user context; mapping the set of file clusters with said processor onto a visualization model; graphically displaying the contents of the computer file system on the graphical user interface using said visualization model, wherein said graphical display depicts a relationship between contents of the computer file system at least partially based upon said user context; wherein the computer file system has a programming interface adapted for displaying file system information on the graphical user interface, and wherein the visualization model is graphically displayed on the graphical user interface by overriding the programming interface; and wherein the visualization model is at least one of a network visualization model, an orbital visualization model, and a mind map. 3. The method of claim 1 , further comprising receiving a search request from the user, and wherein the user context is at least partially determined by the search request. | 0.590535 |
22. The method of claim 21 , further comprising: informing the user of an incorrect pronunciation if the confidence level is not less than the acceptance limit for the at least one incorrectly pronounced phrase. | 22. The method of claim 21 , further comprising: informing the user of an incorrect pronunciation if the confidence level is not less than the acceptance limit for the at least one incorrectly pronounced phrase. 23. The method of claim 22 , wherein the informing of the user of the incorrect pronunciation includes informing the user of at least one incorrectly pronounced uttered phrase, the at least one incorrectly pronounced uttered phrase corresponding to all uttered phrases with corresponding confidence levels that are not less than the associated acceptance limit for the at least one incorrectly pronounced phrase. | 0.829499 |
11. A computer program product comprising a non-transitory tangible computer usable storage medium having readable program code embodied in the non-transitory tangible computer usable storage medium, the computer program product includes at least one component operable to: determine an attribute of a current character in input text, the attribute of the current character indicating one or more classes of characters the current character is assigned thereto; determine one or more attributes of one or more next characters in the input text, the one or more attributes of the one or more next characters indicating the one or more classes the one or more next characters are assigned thereto; and construct a token of the input text that comprises the current character and the one or more next characters, the attribute of the current character and the one or more attributes of the one or more next characters intersecting with each other, and the attribute of the current character and the one or more attributes of the one or more next characters comprising an attribute data structure which comprises a one-byte array, wherein the one-byte array comprises a plurality of binary bits and each bit of the binary bits indicates a different class from remaining bits of the binary bits. | 11. A computer program product comprising a non-transitory tangible computer usable storage medium having readable program code embodied in the non-transitory tangible computer usable storage medium, the computer program product includes at least one component operable to: determine an attribute of a current character in input text, the attribute of the current character indicating one or more classes of characters the current character is assigned thereto; determine one or more attributes of one or more next characters in the input text, the one or more attributes of the one or more next characters indicating the one or more classes the one or more next characters are assigned thereto; and construct a token of the input text that comprises the current character and the one or more next characters, the attribute of the current character and the one or more attributes of the one or more next characters intersecting with each other, and the attribute of the current character and the one or more attributes of the one or more next characters comprising an attribute data structure which comprises a one-byte array, wherein the one-byte array comprises a plurality of binary bits and each bit of the binary bits indicates a different class from remaining bits of the binary bits. 14. The computer program product of claim 11 , wherein the at least one component is further operable to receive the input text from at least one of a local component of the computer program product, a user device, and a third party server. | 0.642483 |
16. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: identify a plurality of documents, a first document, of the plurality of documents, being linked to by a second document, of the plurality of documents, the second document and a third document, of the plurality of documents, being in a set of affiliated documents; calculate a first value for each document in the set of affiliated documents, calculating the first value for each document in the set of affiliated documents being based on: a ranking score of the document, and a number of outbound links from the document; determine that the first value calculated for the third document is a maximum of the first values calculated for each document in the set of affiliated documents; assign a ranking score to the first document based the first value calculated for the third document; and store the ranking score. | 16. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: identify a plurality of documents, a first document, of the plurality of documents, being linked to by a second document, of the plurality of documents, the second document and a third document, of the plurality of documents, being in a set of affiliated documents; calculate a first value for each document in the set of affiliated documents, calculating the first value for each document in the set of affiliated documents being based on: a ranking score of the document, and a number of outbound links from the document; determine that the first value calculated for the third document is a maximum of the first values calculated for each document in the set of affiliated documents; assign a ranking score to the first document based the first value calculated for the third document; and store the ranking score. 18. The non-transitory computer-readable medium of claim 16 , where the instructions further comprise: one or more instructions that, when executed by the one or more processors, cause the one or more processors to: identify affiliations among a plurality of documents in the affiliated set of documents based on at least one of: a link graph structure of the plurality of documents in the affiliated set of documents, traffic patterns associated with the plurality of documents in the affiliated set of documents, similarity of hostnames of the plurality of documents in the affiliated set of documents, or similarity of Internet Protocol (IP) addresses of the plurality of documents in the affiliated set of documents. | 0.506112 |
1. A system providing access to a directory services repository which is stored on a computer system, the claimed system comprising: a directory services application programming interface, also known as the API, which includes at least one callable element that is capable of accessing a component of the directory services repository in response to being called; and a driver which is capable of translating a relational database language statement into an executable API sequence that includes a call to the callable element and produces an API result, the driver also being capable of translating the API result into a relational database result, wherein the directory services repository component includes an effective class and an object having a context the relational database language statement identifies a table and a subset restriction, and the driver and the API together map the effective class to the table and also map the context to the subset restriction. | 1. A system providing access to a directory services repository which is stored on a computer system, the claimed system comprising: a directory services application programming interface, also known as the API, which includes at least one callable element that is capable of accessing a component of the directory services repository in response to being called; and a driver which is capable of translating a relational database language statement into an executable API sequence that includes a call to the callable element and produces an API result, the driver also being capable of translating the API result into a relational database result, wherein the directory services repository component includes an effective class and an object having a context the relational database language statement identifies a table and a subset restriction, and the driver and the API together map the effective class to the table and also map the context to the subset restriction. 12. The system of claim 1, wherein the driver and the API allow an application program to discover the number of rows of the table by visiting each object, if any, which is an instance of the effective class, until a "no more date" indication is returned because each object, if any, has been accessed. | 0.574013 |
6. A method of providing music within a motor vehicle, the method comprising: using a microphone to produce a microphone signal based upon lyrics of a song uttered by a human passenger within a passenger compartment of the motor vehicle; using a voice recognition module to ascertain the lyrics uttered by the human passenger; retrieving Karaoke music corresponding to the ascertained lyrics uttered by the human passenger; playing the Karaoke music on a loudspeaker associated with the passenger compartment; and continuing to ascertain the lyrics being uttered by the human passenger while the Karaoke music is being retrieved, wherein the playing step includes beginning to play the Karaoke music on the loudspeaker at a point in the music that corresponds to a point at which the passenger is currently singing within the song. | 6. A method of providing music within a motor vehicle, the method comprising: using a microphone to produce a microphone signal based upon lyrics of a song uttered by a human passenger within a passenger compartment of the motor vehicle; using a voice recognition module to ascertain the lyrics uttered by the human passenger; retrieving Karaoke music corresponding to the ascertained lyrics uttered by the human passenger; playing the Karaoke music on a loudspeaker associated with the passenger compartment; and continuing to ascertain the lyrics being uttered by the human passenger while the Karaoke music is being retrieved, wherein the playing step includes beginning to play the Karaoke music on the loudspeaker at a point in the music that corresponds to a point at which the passenger is currently singing within the song. 10. The method of claim 6 wherein the Karaoke music includes only instrumental music without any human voice. | 0.854497 |
16. One or more storage media storing instructions which, when executed by one or more processors, cause: determining a first context from among a plurality of contexts; based on the first context, identifying a first technique for analyzing text data, wherein each context of the plurality of contexts is associated with a different technique for analyzing text data; using the first technique to analyze a string of text that was generated based on audio data; wherein using the first technique comprises identifying a plurality of text segments based on one or more criteria, wherein each segment of the plurality of text segments comprises one or more words in the string of text, wherein at least one text segment of the plurality of text segments comprises a plurality of words; organizing the plurality of text segments into a list of items, wherein each text segment is a separate item in the list. | 16. One or more storage media storing instructions which, when executed by one or more processors, cause: determining a first context from among a plurality of contexts; based on the first context, identifying a first technique for analyzing text data, wherein each context of the plurality of contexts is associated with a different technique for analyzing text data; using the first technique to analyze a string of text that was generated based on audio data; wherein using the first technique comprises identifying a plurality of text segments based on one or more criteria, wherein each segment of the plurality of text segments comprises one or more words in the string of text, wherein at least one text segment of the plurality of text segments comprises a plurality of words; organizing the plurality of text segments into a list of items, wherein each text segment is a separate item in the list. 17. The one or more storage media of claim 16 , wherein the instructions, when executed by the one or more processors, further cause causing the list to be displayed on a computer display device. | 0.684172 |
13. A storage device comprising instructions that are readable by a processor to cause said processor to perform actions of: receiving input data that includes (a) a string of characters in a first language, and (b) semantic contextual data concerning a source of said input data; parsing said string of characters into its graphemes; generating a pattern of characters that represents an abstraction of said graphemes; analyzing said semantic contextual data and said pattern of characters in accordance with rules, to yield a potential interlingual transformation of said pattern of characters; transforming said string of characters from said first language into a second language in accordance with said potential interlingual transformation, thus yielding a transformation; analyzing performance indicia about said transformation; and updating said rules based on said performance indicia. | 13. A storage device comprising instructions that are readable by a processor to cause said processor to perform actions of: receiving input data that includes (a) a string of characters in a first language, and (b) semantic contextual data concerning a source of said input data; parsing said string of characters into its graphemes; generating a pattern of characters that represents an abstraction of said graphemes; analyzing said semantic contextual data and said pattern of characters in accordance with rules, to yield a potential interlingual transformation of said pattern of characters; transforming said string of characters from said first language into a second language in accordance with said potential interlingual transformation, thus yielding a transformation; analyzing performance indicia about said transformation; and updating said rules based on said performance indicia. 14. The storage device of claim 13 , wherein said pattern of characters includes a group of characters that corresponds to a grapheme in said graphemes, and that is mapped to said source. | 0.731613 |
1. A computer readable storage device encoded with a computer program, the program comprising instructions that when executed by a data processing apparatus cause the data processing apparatus to perform operations comprising: receiving, by the data processing apparatus that is operating in a locked mode, audio data that encodes an utterance of a user, wherein the locked mode prevents the data processing apparatus from performing at least one action; providing, while the data processing apparatus is operating in the locked mode, the audio data to a voice biometric engine and a voice action engine; receiving, while the data processing apparatus is operating in the locked mode, data from the voice action engine that identifies a voice action that is associated with the utterance; determining, while the data processing apparatus is operating in the locked mode, that the voice action that is associated with the utterance is classified as a voice action that requires authentication to perform; based on determining that the voice action that is associated with the utterance is classified as a voice action that requires authentication to perform, queuing, while the data processing apparatus is operating in the locked mode, data that identifies the voice action that is associated with the utterance; after queuing the data that identifies the voice action that is associated with the utterance, receiving, while the data processing apparatus is operating in the locked mode, an indication from the voice biometric engine that the user has been biometrically authenticated; and in response to receiving the indication, placing the data processing apparatus in an unlocked mode, and triggering the voice action engine to process the queued action that is associated with the utterance. | 1. A computer readable storage device encoded with a computer program, the program comprising instructions that when executed by a data processing apparatus cause the data processing apparatus to perform operations comprising: receiving, by the data processing apparatus that is operating in a locked mode, audio data that encodes an utterance of a user, wherein the locked mode prevents the data processing apparatus from performing at least one action; providing, while the data processing apparatus is operating in the locked mode, the audio data to a voice biometric engine and a voice action engine; receiving, while the data processing apparatus is operating in the locked mode, data from the voice action engine that identifies a voice action that is associated with the utterance; determining, while the data processing apparatus is operating in the locked mode, that the voice action that is associated with the utterance is classified as a voice action that requires authentication to perform; based on determining that the voice action that is associated with the utterance is classified as a voice action that requires authentication to perform, queuing, while the data processing apparatus is operating in the locked mode, data that identifies the voice action that is associated with the utterance; after queuing the data that identifies the voice action that is associated with the utterance, receiving, while the data processing apparatus is operating in the locked mode, an indication from the voice biometric engine that the user has been biometrically authenticated; and in response to receiving the indication, placing the data processing apparatus in an unlocked mode, and triggering the voice action engine to process the queued action that is associated with the utterance. 3. The computer storage device of claim 1 , wherein the voice action is completed by the voice action engine without requiring the user to speak another utterance after the user has been biometrically authenticated. | 0.678618 |
7. The computer system of claim 1 , wherein each concept in said vector form a pattern. | 7. The computer system of claim 1 , wherein each concept in said vector form a pattern. 8. The computer system of claim 7 , wherein said comparing data in said electronic claim file to said elements in said vector further comprise comparing said pattern to a stored set of patterns. | 0.903274 |
49. The apparatus of claim 48 , wherein instructions to determine an appropriate response template comprise instructions to: divide the input into word segments; traverse the attribute trie with the input to determine matching attributes; traverse the “that” trie to determine matching “that” patterns from a previous output; and traverse the megacategory trie with matching attributes patterns and matching “that” patterns to determine matching megacategories. | 49. The apparatus of claim 48 , wherein instructions to determine an appropriate response template comprise instructions to: divide the input into word segments; traverse the attribute trie with the input to determine matching attributes; traverse the “that” trie to determine matching “that” patterns from a previous output; and traverse the megacategory trie with matching attributes patterns and matching “that” patterns to determine matching megacategories. 54. The apparatus of claim 49 , further comprising instructions to: determine that no megacategories match, add matched attributes from a last user input to the current matched attributes; and determine a matching megacategory. | 0.649522 |
16. The method of claim 15 wherein the third metric value is generated based on the number of times a regional result was selected relative to the number of times a global result was selected from the plurality of results. | 16. The method of claim 15 wherein the third metric value is generated based on the number of times a regional result was selected relative to the number of times a global result was selected from the plurality of results. 17. The method of claim 16 further comprising determining that the first search query is regional specific query when the third metric value exceeds a RCR threshold. | 0.915805 |
1. A computer-implemented method comprising: identifying, at a computer device, a request for electronic content, wherein the electronic content is available to the computer device through a network; analyzing, locally at the computer device, the electronic content to determine a content score of the electronic content based on at least one of a banned keyword count and a weighted banned keyword count; blocking, at the computer device, access to the electronic content on the computer device if the content score is below a minimum threshold; allowing, at the computer device, access to the electronic content on the computer device if the content score is above a maximum threshold; requesting, from the computer device, that a remote device perform a remote analysis of the electronic content if it the content score is between the minimum threshold and the maximum threshold, wherein the remote analysis is a more computationally-intensive analysis as compared to the local analysis, and wherein at least one of the minimum threshold and the maximum threshold is adjusted according to one or more performance constraints of the computer device. | 1. A computer-implemented method comprising: identifying, at a computer device, a request for electronic content, wherein the electronic content is available to the computer device through a network; analyzing, locally at the computer device, the electronic content to determine a content score of the electronic content based on at least one of a banned keyword count and a weighted banned keyword count; blocking, at the computer device, access to the electronic content on the computer device if the content score is below a minimum threshold; allowing, at the computer device, access to the electronic content on the computer device if the content score is above a maximum threshold; requesting, from the computer device, that a remote device perform a remote analysis of the electronic content if it the content score is between the minimum threshold and the maximum threshold, wherein the remote analysis is a more computationally-intensive analysis as compared to the local analysis, and wherein at least one of the minimum threshold and the maximum threshold is adjusted according to one or more performance constraints of the computer device. 9. The method of claim 1 , wherein performance of the computer device is improved by adjusting at least one of the minimum threshold and the maximum threshold. | 0.597482 |
8. The computer-readable storage medium according to claim 6 , wherein the method performed by the computer-executable instructions stored on the computer-readable medium further comprises: arranging the transcribed metadata items into a plurality of subsets of transcribed first and second metadata items based on the filter criteria; and storing the plurality of subsets in a computer-readable memory, the plurality of subsets stored at single location or in a distributed fashion. | 8. The computer-readable storage medium according to claim 6 , wherein the method performed by the computer-executable instructions stored on the computer-readable medium further comprises: arranging the transcribed metadata items into a plurality of subsets of transcribed first and second metadata items based on the filter criteria; and storing the plurality of subsets in a computer-readable memory, the plurality of subsets stored at single location or in a distributed fashion. 9. The computer-readable storage medium according to claim 8 , wherein the computer-readable memory is selected from the group consisting of: a client-side temporary or persistent memory, or network-side temporary or persistent memory. | 0.942501 |
4. The method for controlling a printer in a networked environment utilizing printer usage statistics and document features according to claim 1 , further comprising: retrieving user specific information from the print server; and obtaining print settings information from at least one printer. | 4. The method for controlling a printer in a networked environment utilizing printer usage statistics and document features according to claim 1 , further comprising: retrieving user specific information from the print server; and obtaining print settings information from at least one printer. 9. The method for controlling a printer in a networked environment utilizing printer usage statistics and document features according to claim 4 , further comprising utilizing said user specific information and said print settings information to determine whether printing of said document is necessary. | 0.904822 |
1. A method to provide internet-based services targeted to a geographic location, the method comprising: receiving a request from a user to provide internet-based services based on a target geographic location; obtaining a plurality of candidate geographic locations associated with the user, each candidate geographic location being associated with a respective candidate confidence level; calculating, with a computer, for one of the candidate geographic locations, a respective aggregate probabilistic utility score, the aggregate probabilistic utility score being based, at least in part, on distances from the respective candidate geographic location to the other candidate geographic locations and the confidence level scores of the other candidate geographic locations; selecting a geographic location based, at least in part, on the aggregate probabilistic utility score from among the candidate geographic locations; and providing internet-based services to the user targeting the selected geographic location. | 1. A method to provide internet-based services targeted to a geographic location, the method comprising: receiving a request from a user to provide internet-based services based on a target geographic location; obtaining a plurality of candidate geographic locations associated with the user, each candidate geographic location being associated with a respective candidate confidence level; calculating, with a computer, for one of the candidate geographic locations, a respective aggregate probabilistic utility score, the aggregate probabilistic utility score being based, at least in part, on distances from the respective candidate geographic location to the other candidate geographic locations and the confidence level scores of the other candidate geographic locations; selecting a geographic location based, at least in part, on the aggregate probabilistic utility score from among the candidate geographic locations; and providing internet-based services to the user targeting the selected geographic location. 12. The method of claim 1 , wherein calculating an aggregate probabilistic utility score further comprises: obtaining a trip-utility factor indicative of utility of a trip to one of the other candidate geographic locations to the user irrespective of distance; and calculating the aggregate probabilistic utility score based on the trip-utility factor. | 0.678302 |
4. A method performed by a specifically programmed computer system for determining a statistical sentiment associated with an entity, the method comprising: inputting a plurality of texts associated with the entity; inputting a sentiment lexicon comprising a plurality of terms each associated with a positive or negative polarity and each associated with a subjectivity score; determining, using the specifically programmed computer system, an entity polarity for the plurality of texts processed based on polarity of terms in the sentiment lexicon which are associated with text corresponding to the entity in the plurality of texts; determining an entity subjectivity for the plurality of texts processed based on subjectivity scores of terms in the sentiment lexicon which are associated with text corresponding to the entity in the plurality of texts; determining an entity statistical sentiment based on the entity polarity and entity subjectivity; and outputting the entity statistical sentiment. | 4. A method performed by a specifically programmed computer system for determining a statistical sentiment associated with an entity, the method comprising: inputting a plurality of texts associated with the entity; inputting a sentiment lexicon comprising a plurality of terms each associated with a positive or negative polarity and each associated with a subjectivity score; determining, using the specifically programmed computer system, an entity polarity for the plurality of texts processed based on polarity of terms in the sentiment lexicon which are associated with text corresponding to the entity in the plurality of texts; determining an entity subjectivity for the plurality of texts processed based on subjectivity scores of terms in the sentiment lexicon which are associated with text corresponding to the entity in the plurality of texts; determining an entity statistical sentiment based on the entity polarity and entity subjectivity; and outputting the entity statistical sentiment. 6. The method of claim 4 , further comprising: determining a world subjectivity based on subjectivity scores of terms in the sentiment lexicon in the plurality of texts and normalizing the entity subjectivity based on the world subjectivity. | 0.82232 |
3. The system as recited in claim 1 , wherein the platform-independent language is Java™. | 3. The system as recited in claim 1 , wherein the platform-independent language is Java™. 5. The system as recited in claim 3 , wherein the generated stub includes Java™ bytecode configured to, when the native language function is called by a Java™ function at runtime: record top of a current thread's local stack; retrieve a pointer to a thread local environment data structure and put the pointer onto the stack as a parameter to the native language function; wrap each of one or more reference parameters in a handle and put each of the one or more wrapped reference parameters onto the stack; call the native language function; if the native language function returns a value, unwrap the returned value from a handle in which it is wrapped; restore the top of the current thread's local stack; throw any pending exceptions; and return to the calling Java™ function. | 0.670742 |
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