Why known Um I already told me it before she told you No she told me a long time ago Oh She well me doesn't matter told what me time weeks ago OK You know how to Wow toggle she the hadn't display started width transcribing me yet Anyway What is it Let me explain something to you Um function than yours there Yo beg to differ Um OK Yeah something genuinely funny before get an example The thing is I don't know how No get to the next page Here You should be at least be Actually I thought enough to laugh at your own jokes There No a different laugh How weird wow Oh Wow What mackerel Oh OK I wasn't even doing anything OK Uh got a laptop trying to show it off That was r actually idea But anyhow Um So here we are Once again Once again right together Um so we haven't had a meeting for a while and and probably won't have one next week I think a number of people are gone Um so Robert why don't you bring us up to date on where we are with EDU Um uh in a in a smaller group we had uh talked and decided about continuation of the data collection So time with us is almost officially over and she brought us some thirty subjects and t collected the data and ten dialogues have been transcribed and can be looked at If interested in that talk to me Um and we found another uh cogsci student interested in playing wizard for us Here gonna make it a little bit more complicated for the subjects uh this round actually suggested to look um at the psychology department students because they have to partake in two experiments in order to fulfill some requirements So they have to be subjected before they can actually graduate And um we want to design it so that they really have to think about having some time two days for example to plan certain things and figure out which can be done at what time and um sort of package the whole thing in a in a re in a few more complicated um structure for the data collection As for SmartKom the last SmartKom meeting I mentioned that we have some problems with the synthesis which as of this morning should be resolved Good And so should be means they aren't yet but but I think I have the info now that I need Plus Johno and I are meeting tomorrow so maybe uh uh when tomorrow is over done And ha n hav never have to look at it again Maybe take some more time to be realistic but at least seeing the end of the tunnel there That was that Um the uh uh I don't think we need to discuss the formalism be done officially s once done Um something happened in on side with the PRM that gonna look at today and um we have a visitor from Bruchsal from the International University Andreas I think met everyone except Nancy Yeah Hi Hi Hi Hi And you um said Andreas I thought you were talking about Stolcke Now I know that we aren't OK Andy you actually go by Andy right Oh OK Cuz there is another Andreas around Hmm to avoid some confusion That will be Reuter Yeah Oh OK So my scientific director of the EML is also the dean of the International University one of his many occupations that just contributes to the fact that he is very occupied And um the um he might tell us a little bit about what actually doing and why it is s somewhat related and by uh using maybe some of the same technologies that we are using And um Was that enough of an update I think so In what order shall we proceed OK Maybe you have your Uh yeah sure Um so be just been looking at um Ack What are you doing Yeah OK Um been looking at the PRM stuff Um so this is sort of like the latest thing I have on it and I sorta constructed a couple of classes Like a user class a site class and and you know a time a route and then and a query class And I tried to simplify it down a little bit so that I can actually um look at it more the same paper that I gave to Jerry last time Um so basically I took out a lot of stuff a lot of the decision nodes and then tried to The red lines on the um graph are the um relations between the different um classes Like a user has like a query and then also has you know um reference slots to its preferences um the special needs and you know money and the user interest And so this is more or less similar to the flat that I have you know with the input nodes and all that And So I tried to construct the dependency models and a lot of these stuff I got from the flat and what they depend on and it turns out you know the are really big if I do that so I tried to see how I can do um put in the computational nodes in between And what that would look like in a PRM And so I ended up making several classes Actually you know a class of with different attributes that are the intermediate nodes and one of them is like time affordability money affordability site availability and the travel compatibility And so some of these classes are s some of these attributes only depend on stuff from say the user or s f just from I don't know like the site S like um these here only like user but if you look at travel compatibility for each of these factors you need to look at a pair of you know what the um preference of the user is versus you know what type of an event it is or you know which form of transportation the user has and whether you know the onsite parking matters to the user in that case And that makes the scenario a little different in a PRM because um then you have objects and potentially you can have many different sites in in mind And so for each of the site come up with this rating of travel compatibility And they all depend on the same users but different sites and that makes a tr I w I wa have been trying to see whether the PRM would make it more efficient if we do inferencing like that And so I guess you end up having fewer number of nodes than in a flat cuz otherwise you would c well probably the same But um No you would definitely have be able to like um