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false | Um - hmm , um , well , first of all uh , uh , great looks , mu much cleaner , nnn , nnn , Certain certain beauty in it , so , um , if beauty is truth , then , uh we 're in good shape. But , the um , as , uh , mentioned before we probably should look at t the details. So if you have a write - up then uh , I 'd love to read it | QMSum_45 |
false | Mm - hmm. | QMSum_45 |
false | and uh because , um , i Can you go all the way back to the the very top ? | QMSum_45 |
false | Yeah. | QMSum_45 |
false | Um , uh these @ @ these w w when these are instantiated they take on the same values ? that we had before ? | QMSum_45 |
false | I can't really see the whole thing. | QMSum_45 |
false | or are they have they changed , in a sense ? | QMSum_45 |
false | Well I think I basically leave them to similar things. | QMSum_45 |
false | Uh - huh. | QMSum_45 |
false | Some of the things might that might be different , maybe like are that the hours for the site. | QMSum_45 |
false | Hmm. | QMSum_45 |
false | And , eventually I meant that to mean whether they 're open at this hour or not. | QMSum_45 |
false | Uh - huh. | QMSum_45 |
false | And status would be , you know , more or less like , whether they 're under construction , and and or stuff like that. | QMSum_45 |
false | And the , uh , other question I would have is that presumably , from the way the Stanford people talk about it , you can put the probabilities also on the relations. If | QMSum_45 |
false | Which is the structural uncertainty ? | QMSum_45 |
false | Yeah. Yeah , I that 's That I think was actually in the previous the Ubenth stuff. I don't remember whether they carried that over to this or not , | QMSum_45 |
false | Mmm. | QMSum_45 |
false | uh , structural uncertainty. | QMSum_45 |
false | It 's sort of in the definition or in the in Daphne 's definition of a PRM is that classes and relations , | QMSum_45 |
false | OK. | QMSum_45 |
false | and you 're gonna have CPT 's over the classes and their relations. | QMSum_45 |
false | Alright. | QMSum_45 |
false | More uncertainty , or or | QMSum_45 |
false | Uh , | QMSum_45 |
false | I should say. | QMSum_45 |
false | I remember them learning when , you know , you don't know the structure for sure , | QMSum_45 |
false | Yeah. | QMSum_45 |
false | but I don't remember reading how you specify | QMSum_45 |
false | Yeah , that would be exactly my question. | QMSum_45 |
false | Right. | QMSum_45 |
false | wh to start with. Yeah. | QMSum_45 |
false | Well | QMSum_45 |
false | Yeah. | QMSum_45 |
false | Yeah. So , uh , the the plan is is when Daphne gets back , we 'll get in touch and supposedly , um , we 'll actually get s deep seriously connected to to their work and | QMSum_45 |
false | Yep. | QMSum_45 |
false | somebody 'll Uh , you know If it 's a group meeting once a week probably someone 'll go down and , whatever. So , we 'll actually figure all this out. | QMSum_45 |
false | OK. OK. Then I think the w long term perspective is is pretty clear. We get rocking and rolling on this again , once we get a package , if , when , and how , then this becomes foregrounded | QMSum_45 |
false | Mm - hmm. | QMSum_45 |
false | profiled , focused , again. | QMSum_45 |
false | Designated ? | QMSum_45 |
false | Of course. | QMSum_45 |
false | And um , until then we 'll come up with a something that 's @ @ that 's way more complicated for you. Right ? | QMSum_45 |
false | OK. | QMSum_45 |
false | Because this was laughingly easy , right ? | QMSum_45 |
false | Actually I had to take out a lot of the complicated stuff , cuz I I made it really complicated in the beginning , and Jerry was like , " this is just too much ". | QMSum_45 |
false | Yeah. So , um , you could , from this , go on and say suppose there 's a group of people traveling together and you wanted to plan something that somehow , with some Pareto optimal uh , uh , thing for | QMSum_45 |
false | That 's good. That 's definitely a job for artificial intelligence. | QMSum_45 |
false | uh , or | QMSum_45 |
false | Except for humans can't really solve it either , so. | QMSum_45 |
false | Well that 's not not even something humans yeah. | QMSum_45 |
false | Right. Right. Well that 's the that would that would be a uh , you could sell it , as a | QMSum_45 |
false | Yeah. | QMSum_45 |
false | OK , eh you don't have to fight about this , just give your preferences to the | QMSum_45 |
false | And then you can blame the computer. | QMSum_45 |
false | w Exactly. | QMSum_45 |
false | So. | QMSum_45 |
false | Hmm. But what does it uh Would a pote potential result be to to split up and never talk to each other again ? You know. | QMSum_45 |
false | That should be one of them. | QMSum_45 |
false | Yeah. | QMSum_45 |
false | Yeah. Right. | QMSum_45 |
false | That 'd be nice. | QMSum_45 |
false | Mmm. | QMSum_45 |
false | Anyway. So. So there i there are some some u uh , you know , uh , elaborations of this that you could try to put in to this structure , but I don't think it 's worth it now. Because we 're gonna see what what else uh what else we 're gonna do. Anyway. But uh , it 's good , yeah and and there were a couple other ideas of of uh , things for Eva to look at in in the interim. | QMSum_45 |
false | Good. Then , we can move on and see what Andreas has got out his sleeve. Or Andy , for that matter ? | QMSum_45 |
true | OK. So uh , uh , well , thanks for having me here , first of all. Um , so maybe just a a little background on on my visit. So , uh , I 'm not really involved in any project , that 's uh that 's relevant to you uh , a at the moment , uh , the the reason is really for me uh , to have an opportunity to talk to some other researchers in the field. And and so I 'll just n sort of give you a real quick introduction to what I 'm working on , and um , I just hope that you have some comments or , maybe you 're interested in it to find out more , and and so I 'll be uh , happy to talk to you and and uh , I 'd also like to find out some more and and maybe I 'll just walk around the office and and then and ask some some questions , uh , in a couple days. So I 'll be here for uh , tomorrow and then uh , the remainder of uh , next week. OK , so , um , what I started looking at , uh , to begin with is just uh , content management systems uh , i i in general. So um , uh what 's uh Sort of the state of the art there is to um uh you have a bunch of of uh documents or learning units or learning objects , um , and you store meta - data uh , associate to them. So there 's some international standards like the I - triple - E , uh There 's an I - triple - E , LON standard , and um , these fields are pretty straightforward , you have uh author information , you have uh , size information , format information and so on. Uh , but they 're two uh fields that are um , more interesting. One is uh you store keywords associated with the uh with the document , and one is uh , you have sort of a , um , well , what is the document about ? So it 's some sort of taxonomic uh , ordering of of the of the units. Now , if you sort of put on your semantic glasses , uh you say , well that 's not all that easy , because there 's an implicit um , uh , assumption behind that is that uh , all the users of this system share the same interpretation of the keyword and the same interpretation of uh , whichever taxonomy is used , and uh , I think that 's a that 's a very that 's a key point of these systems and they sort of always brush over this real quickly without really elaborating much of that and uh As a matter of fact , the only thing that m apparently really works out so far are library ordering codes , which are very , very coarse grain , so you have some like , science , biology , and then But that 's really all that we have at the moment. So I think there 's a huge , um , uh need for improvement there. Now , what this uh a standard like this would give us is we could um , sort of uh with a search engine just query uh , different repositories all over the world. But we can't really Um , so what I 'm what I try to do is um , to have um , uh So. So the scenario is the following , you you 're working on some sort of project and you encounter a certain problem. Now , what what we have at our university quite a bit is that uh , students um , try to u program a certain assignment , for example , they always run into the same problems , uh , and they always come running to us , and they 'll say why 's it not it 's not working , and we always give out the same answer , so we thought , well , it 'd be nice to have a system that could sort of take care of this , and so , what I want to build is basically a a smart F A Q system. Now , what you uh need to do here is you need to provide some context information which is more elaborate than " I 'm looking for this and this and this keyword. " So. And I think that I don't need to tell you this. I 'm I 'm sure you have the same when when somebody utters a sentence in a certain , uh , context it , and and the same sentence in another context makes a huge difference. So , I want to be able to model information like , um , so in the in the context of in the context of developing distributed systems , of a at a computer science school , um , what kind of software is the person using , which homework assignment is he or she working on at the moment , um , maybe what 's the background of that student 's um , which um , which error message was encountered. So this sort of information I think should be transmitted , uh , when a certain document is retrieved. Now , um , basically giving this um Uh so we somehow need to have a formalized um , way of writing this down basically , and that 's where the shared interpretation of of certain terms and keywords comes in again. And , using this and some some uh , knowledge about the domain I think you can do some some simple inferences. Like you know that when somebody 's working about uh , working on on servlets for example , he 's using Java , cuz servlets are used are written in Java. So some some inferences like that , now , um , u using this you can infer more information , and you could then match this to the meta - data of um off the documents you 're you 're searching against. So , uh what I wanna do is basically have some sort of um given these inputs , and then I can compute how many documents match , and use this as a metric in the search. Now , what I plan to do is I want to uh sort of do a uh uh try to improve the quality of the search results , and I want to do this by having a depth uh , um , um steepest descent approach. So if I knew which operating system the person was working on , would this improve my search result ? And and having uh , uh a symbolic formalized model of this I could simply compute that , and find out which um which questions are worth um , asking. And that 's what I then propagate back to the user , and and sort of try to optimize the search in this way. Now , the big problem that I 'm facing right now is um , it 's fairly easy to hack up a system uh quickly , that that works in the small domain , but the problem is obviously the scalability. And uh uh , so Robert was mentioning uh , earlier today is that uh , Microsoft for example with their printer set up program has a Bayesian network , which does exactly this , but there you face a problem that these are very hard to extend. And so , uh what I 'm What I try to do is basically try to model this uh , in a way that you could really combine uh , knowledge from very different sources , and and um , sort of looking into some of the ideas that the semantic web community uh , came up with. Trying to to have uh , an approach how to integrate s uh certain uh representation of certain concepts and also some computational rules , um , what you can do with those. Um. What I 'm also looking into is a probabilistic approach into this because document retrievals is a very fuzzy procedure , so it 's probably not that easy to simply have a symbolic uh , computational model. That that probably isn't expressive enough. So. So that 's another thing , um , which I think you 're also uh , uh looking into right now. And then um , uh sort of as an add - on to this whole idea , um , uh that would be now , depending on what the search engine or the content repository depending on which um , uh , which uh , rules and which ontologies it it uses , or basically its view of the world , uh you can get very different results. So it might ma make a lot of sense to actually query a lot of different search engines. And there you could have an idea where you actually have sort of a a peer to peer approach , where we 're all sort of carrying around our individual bookshelves , and um , if you have a question about a homework , it 's probably makes sense to ask somebody who 's in your class with you , sort of the guru in the certain area , rather than going to some Yahoo - like uh , search engine. So these are some of the just in a nutshell , some of the ideas. And I think a lot of the even though it 's a it 's a very different domain , but I think a lot of the , um , issues are are fairly similar. So. OK. | QMSum_45 |
false | And so some of the I don't know how much you know about the larger Heidelberg project , I Are you | QMSum_45 |
false | Uh I know , yeah I know abou about it. | QMSum_45 |
false | So it seems like a lot of some of the issues are the same. It 's like , um , you know , the c context - based factors that influence how you interpret , | QMSum_45 |
false | Mm - hmm. Mm - hmm. | QMSum_45 |
false | um , s how to interpret. In in this case , infer in in knowing wanting to know what kinds of things to ask. We - we 've kind of talked about that , but we haven't worried too much about that end of the discourse. | QMSum_45 |
false | Mm - hmm. | QMSum_45 |
false | But maybe you guys had that in the previous models. | QMSum_45 |
false | Well , in a in one t one s mmm , small difference in a in a way , is that he doesn't have to come up with an answer , but he wants to point to the places w w | QMSum_45 |
false | Documents that have the answers. | QMSum_45 |
false | Yeah , so. So I 'm I 'm not I 'm not building an expert | QMSum_45 |
false | Mm - hmm. | QMSum_45 |
false | Uh , I want to build a smart librarian , basically | QMSum_45 |
false | Right. Right. | QMSum_45 |
false | that can point you to the right reference. I don't wanna compute the answer , so it 's a little bit easier for me. | QMSum_45 |
false | Well. Uh , you have to s still m understand what the content says about itself , and then match it to what you think the informational needs | QMSum_45 |
false | Mm - hmm. | QMSum_45 |
false | Mm - hmm. | QMSum_45 |
false | So you also don't have to figure out what the content is. You 're just taking the keywords as a topic text , as | QMSum_45 |
false | I I assume that that the there will be learning systems that that tag their their content. | QMSum_45 |
false | OK. Right. | QMSum_45 |
false | And um , um , m @ @ and basically what I what I envision is that you rather than just supplying a bunch of keywords you could basically for for an FAQ for example you could state sort of like a logic condition , when this document applies. So " this document explains how to set up your uh , mail account on Linux " or something like this. | QMSum_45 |
false | Mm - hmm. | QMSum_45 |
false | So. So something something very specific that you can then But the I think that the key point with these uh , learning systems is that uh , a learning system is only as good as uh the amount of content it it carries. | QMSum_45 |
false | Mmm , mm - hmm. | QMSum_45 |
false | You can have the best learning system with the best search interface , if there 's no content inside of it , it 's not very useful. So I think ultimately because um , uh developing these these rules and these inference uh inferences I think is very costly , so um , uh I think you must be able to reuse some some existing um , domain domain information , or or or ontologies that that uh other people wrote and then try to integrate them , and then also search the entire web basically , rather than just the small uh , content management system. | QMSum_45 |
false | OK. Mm - hmm. | QMSum_45 |
false | So I think that 's that 's crucial for for the success of or @ @ | QMSum_45 |
false | So , you 're not I guess I 'm trying to figure out how how it maps to the kinds of things that we 've talked about in this group , and , actually associated groups , | QMSum_45 |
false | Mm - hmm. | QMSum_45 |
false | cuz some of us do pretty detailed linguistic analyses , and I 'm guessing that you you won't be doing that ? OK. | QMSum_45 |
false | No. | QMSum_45 |
false | Just checking. So , OK. | QMSum_45 |
false | Hmm. | QMSum_45 |
false | No. | QMSum_45 |
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