Building, Querying & Personalising RDF Resources

Building, Querying & Personalising RDF Resources Gunnar Aastrand Grimnes 21st January, 2003 DDIM Awayday

Overview • Architecture overview. • Information agents. • Static RDF. • Dynamic RDF. • Query by Example. • Personalisation.

Architecture Evening Agent Profile Agent Query By Example RDF Profiles Pub Agent Restaurant Agent Cinema Agent Static RDF Static RDF Generated RDF Scoot.co.uk WWW Perl Hack

The Information Agents • Identical codebase. • RDF config file. • Static and dynamic content. <conf:RDFAgent> <conf:datapath> /home/ggrimnes/jade/data/ </conf:datapath> <conf:datafile>films.rdf</conf:datafile> <conf:datafile>cinemas.rdf</conf:datafile> </conf:RDFAgent>

Static content • Generated either by hand or using Web interface. • Ontologies: • Restaurant, Cinema & Utility from Agentcities. • Pubs, Beer, Eveningplans from Aberdeen.

Web-based RDF Generator • Slow as a dog. • Supports sub/super -class inference. • Limited XML schema datatype support.

Generated RDF <pub:EnglishPub rdf:ID="mypub"> <pub:liveEntertainment rdf:resource="pubs#Never"/> <pub:location> <add:Address rdf:ID="address"> <add:areaName>Mounthooly</add:areaName> <add:buildingName>John Knox Court</add:buildingName> <add:cityName>Aberdeen</add:cityName> <add:countryName>Scotland</add:countryName> <add:doorNumber>7</add:doorNumber> <add:zipCode>AB24 3LF</add:zipCode> <add:locationId> 7, 7</add:locationId> </add:Address> </pub:location> <pub:onLicense>on</pub:onLicense> <pub:pubName>Gunnar's pub</pub:pubName> <pub:pubWebSite>http://www.csd.abdn.ac.uk/pub.php</pub:pubWebSite> <pub:servesBeer rdf:resource="beertypes#grolsch"/> <pub:servesBeer rdf:resource="beertypes#leffeblonde"/> <pub:servesFood>on</pub:servesFood> <pub:telNumber>01224 630538</pub:telNumber> </pub:EnglishPub>

Dynamic Content • Content screen-scraped from Webpage. • RDF generated by Perl script. • Send REQUEST message to make agent reload. • All done in a cron script.

Scoot Example • Belmont • UGC • Lighthouse

Example Film RDF <s:Shows rdf:ID="belmont_BayOfLoveAndSorrowsThe"> <s:time> <s:ShowScheduleCollection>  <s:consistsOf> <s:ShowSchedule> <s:startTime> <c:Calendar> <c:calendarDate> <c:Date> <c:dateDayOfWeek rdf:resource="calendar#Thursday" /> <c:year>2003</c:year> <c:month>1</c:month> </c:Date> </c:calendarDate> <c:calendarTime> <c:Time> <c:format rdf:resource="calendar#24h"/> <c:timeHour>18</c:timeHour> <c:timeMinute>30</c:timeMinute> </c:Time> </c:calendarTime> </c:Calendar> </s:startTime> </s:ShowSchedule> </s:consistsOf> </s:ShowScheduleCollection> </s:time>

Example Film RDF cont. <s:location rdf:resource="cinemas#belmont" /> <s:show> <s:CinemaPerformance rdf:ID="BayOfLoveAndSorrowsThe"> <s:title>Bay Of Love And Sorrows, The</s:title> <s:wwwInformation>http://scoot.co.uk/info?a=5</s:wwwInformation> <s:origin>Canada</s:origin> <s:duration> <c:Duration> <c:durationHour>1</c:durationHour> <c:durationMinute>35</c:durationMinute> </c:Duration> </s:duration> <s:artist> <s:ArtistCollection> <s:consistsOf> <s:Artist> <s:artistName>Peter Outerbridge</s:artistName> <s:rolevalue rdf:resource="shows_ontology.daml#Actor" /> </s:Artist> </s:consistsOf>... </s:ArtistCollection> </s:artist> <s:description>Certificate: 18</s:description> </s:CinemaPerformance> </s:show> </s:Shows>

RDF Query by Example • RDF for content, RDF for queries. • RDQL is complication to write by hand. • Allows for “smarter” queries than RDQL. • Internal conversion to RDQL. • Different target “audience”: • RDQL for application developers. • QbEx for users of services.

QbEx Conversion to RDQL <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:Restaurant> <r:type rdf:resource=“r#Tandoori" /> <r:open-time> <cif:variable rdf:ID="x"> <cif:varname>x</cif:varname> </cif:variable> </r:open-time> </r:Restaurant> </q:template> <q:constraints> <cif:comparison> <cif:comparison_operator>></cif:comparison_operator> <cif:comparison_op1> <cif:variable rdf:about="#x"/> </cif:comparison_op1> <cif:comparison_op2> <cif:integerconst> <cif:constant_value>1900</cif:constant_value> .. . . • Based on Kit’s RDF encoding of CIF.

QbEx Constraints Converted SELECT ?x WHERE (?x, ?y, ?z), ( ?x, <r # open-time>, ?v_x ), ( ?x, <rdf # type>, <r # restaurant> ), ( ?x, <r # type>, <r # Tandoori> ) AND ( ?v_x > 1900 ) • Supports CIF operators, but no function calls or set operators. • RDQL supports regexp matching, could be useful addition to CIF?

QbEx • What triples should be returned? • What inference could be performed? • Sub classes and properties. • DAML or OWL support? • XML schema datatypes? • More information and downloads at: http://www.csd.abdn.ac.uk/research/AgentCities/QueryByExample

Personalisation • Limited at the moment. • Architecture allows for more sophisticated solutions. • Info from EveningAgent to Profile Agent: • Any supplied user preferences. • F.x: pub that serves “Boddington’s” • Any evening plans turned down. • The final accepted evening plan.

Example RDF Profile <ep:User rdf:about='profileagent#pedwards'> <ep:name>pedwards</ep:name> <ep:pword>****</ep:pword> <ep:preferences> pubs: [ serves="mcewans80" ] pubs: [ serves="mcewans80" ] pubs: [ serves="mcewans80" ] cinemas: [ film="LordOfTheRingsTheTwoTowers" ] </ep:preferences> </ep:User>

PersonalisationThe Future… • Granite Nights was always meant as a personalisation test-bed. • Explore the use of different ML algorithms on semantically marked up data: • Explanation Based Generalisation • Case-Based Learning • Create artificial datasets by creating client agents with specific preferences. • F.x. simulate a geek agent: scifi films & fish’n’chips food.

Questions?

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Building, Querying & Personalising RDF Resources