UM03 - Learning Know..

Learning Knowledge Rich User Models from the Semantic Web Gunnar Aastrand Grimnes User Modeling 2003 – Doctoral Consortium 24th June, 2003

Presentation Overview ,[object Object],[object Object],[object Object],[object Object]

Motivation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Part I - Preliminary Experiments ,[object Object],[object Object],[object Object],[object Object],[object Object],An Empirical Investigation of Learning From the Semantic Web , Pete Edwards, Gunnar AA. Grimnes and Alun Preece – Presented at Semantic Web Mining Workshop at ECML/PKDD, Helsinki, 2002

Issues ,[object Object],[object Object],[object Object],[object Object],[object Object]

Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],% Classifying Machine Learning papers: inClass(A,’ML’) :- publisher(A,'Morgan Kaufmann'), booktitleword(A,learning).

Part II ,[object Object],[object Object],[object Object]

GraniteNights ,[object Object],[object Object],[object Object],[object Object],[object Object],GraniteNights - A Multi-Agent Visit Scheduler Utilising Semantic Web Technology , Gunnar AA. Grimnes , Stuart Chalmers , Pete Edwards and Alun Preece Accepted for CIA2003

Query By Example ,[object Object],[object Object],[object Object],[object Object],<q: Query > <q: template > <akt: Academic > <akt: family-name > Brown </akt: family-name > </akt: Academic > </q: template > </q: Query > SELECT ?x WHERE ( ?x , ?y , ?z ), ( ?x , < rdf # type >, < akt # Academic > ), ( ?x , < akt # family-name >, " Brown " )

QbEx with constraints <q: Query > <q: template > <r: R estaurant > <r: type rdf: resource =“ r#Tandoori " /> <r: open-time > <cif: V ariable rdf: ID =" x "> <cif: varname > x </cif: varname > </cif: V ariable > </r: open-time > </r: R estaurant > </q: template > <q: constraints > <cif: C omparison > <cif: comparison O perator > > </cif: comparison O perator > <cif: comparison O p1 > <cif: V ariable rdf: about =" #x "/> </cif: comparison O p1 > <cif: comparison O p2 > <cif: I ntegerconst > <cif: constant V alue > 1900 </cif: constant V alue > .. . . Give me a Restaurant that is open after X, where X > 1900. i.e. Give me a restaurant open after 7 pm.

GraniteNights Profiling <ep: User rdf: about =“ profileagent#gunnar ” ep: name =“ gunnar ” ep: pword =“ **** ”> <ep: preference > <q: Query > <q: template > <pub: EnglishPub > <pub: servesBeer rdf: resource =“ #flowers ”/> </pub: EnglishPub > ... <ep: interactions > <rdf: Seq ><rdf: li > <ep: Interaction ep: timestamp =“ 20030508T135013 ”> <ep: pref > <q: Query > <q: template > <pub: EnglishPub > <pub: servesBeer rdf: resource =“ #flowers ”/> </pub: EnglishPub > ... <pub: EnglishPub > <pub: servesBeer rdf: resource =“ #hobgoblin ”/> ... <pub: EnglishPub > <pub: servesBeer rdf: resource =“ #flowers ”/> ...

GraniteNights Profiling II ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

The Future – RDF Issues ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

The Future – Problems ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

The Future – Plans ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Rule-ML Example ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Agentcities & the Evening Scenario ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

UM03 - Learning Know..

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