Inferenceon the Semantic Web<br />Myungjin Lee<br />
Artificial Intelligence<br />
Fussy<br />System<br />the intelligence of machines<br />methodology<br />Machine<br />Learning<br />Neural<br />Network<b...
What is Semantic Web?<br />Web<br />target<br />Semantic<br />Web<br />Artificial<br />Intelligence<br />goal<br />the int...
approach<br />Approach of Semantic Web<br />Semantic<br />Web<br />Knowledge<br />Base<br />Approach<br />Logic<br />Sente...
Ontology on the Semantic Web<br />OWL<br />Ontology<br />component<br />SCOT<br />component<br />RDF<br />RDFS<br />vocabu...
Merits of Ontology<br />Database<br />Ontology<br />owl:sameAs<br />¬<br />owl:differentFrom<br />image<br />image<br />di...
Task of Inference<br />Inference<br />being able to derive new data<br />from data that you already know<br />dc:descripti...
Ontology Inference<br />Ontology<br />Inference<br />to derive additional facts to be inferred<br />from instance data and...
TBox Inference<br />TBox<br />Inference<br />Ontology<br />Inference<br />statements<br />that describe a system<br />in t...
ABox Inference<br />Ontology<br />Inference<br />ABox<br />Inference<br />TBox-compliant statements<br />about that vocabu...
Rule Inference<br />Rule<br />Inference<br />to produce valid statements<br />within system<br />based on rule<br />dc:des...
SWRL (Semantic Web Rule Language)<br />SWRL<br />Horn-like<br />Rule<br />Member<br />Submission<br />representation<br />...
Inference Engine for Semantic Web<br />Bossam<br />a forward chaining rule engine supports SWRL<br />dc:description<br />r...
SMART System<br />Intelligence<br />Information<br />System<br />Lab<br />Yonsei<br />University<br />java framework for s...
Example Demo<br />SWRL Rule<br />if	sioc:Post(?x)<br />sioc:Post(?y)<br />sioc:topic(?x, ?a)<br />sioc:topic(?y, ?b)<br />...
Issue of Inference<br />RDF 상에서 어디에 추론을 쓰지?<br />새로운 관계 발견을 통한 네트워크 분석<br />또 다른 RDF Vocabularies 혹은 도메인 온톨로지와의 관계 규칙 정의 및...
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Inference on the Semantic Web

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Inference on the Semantic Web

  1. 1. Inferenceon the Semantic Web<br />Myungjin Lee<br />
  2. 2. Artificial Intelligence<br />
  3. 3. Fussy<br />System<br />the intelligence of machines<br />methodology<br />Machine<br />Learning<br />Neural<br />Network<br />goal<br />methodology<br />hasApproach<br />Artificial<br />Intelligence<br />Genetic<br />Algorithm<br />methodology<br />Knowledge<br />Base<br />Approach<br />Logic<br />hasApproach<br />basedon<br />Approaches of AI<br />
  4. 4. What is Semantic Web?<br />Web<br />target<br />Semantic<br />Web<br />Artificial<br />Intelligence<br />goal<br />the intelligence of machines<br />purpose<br />a vision of information<br />that is understandable by computers,<br />so that they can perform<br />more of the tedious work involved<br />in finding, sharing, and combining information<br />on the web.<br />dc:description<br />
  5. 5. approach<br />Approach of Semantic Web<br />Semantic<br />Web<br />Knowledge<br />Base<br />Approach<br />Logic<br />Sentence<br />basedon<br />basedon<br />use<br />representation<br />representation<br />Ontology<br />representation<br />Propositional<br />Logic<br />Predicate<br />Logic<br />Fist Order<br />Logic<br />Description<br />Logic<br />partOf<br />partOf<br />
  6. 6. Ontology on the Semantic Web<br />OWL<br />Ontology<br />component<br />SCOT<br />component<br />RDF<br />RDFS<br />vocabulary<br />component<br />SKOS<br />dc:description<br />XML<br />component<br />vocabulary<br />SIOC<br />URI<br />An ontology is a formal<br />explicit specification of<br />a conceptualization.<br />FOAF<br />
  7. 7. Merits of Ontology<br />Database<br />Ontology<br />owl:sameAs<br />¬<br />owl:differentFrom<br />image<br />image<br />differences<br />differences<br />rdf:Bag<br />rdf:li<br />rdf:li<br />rdf:li<br />a power<br />of<br />represen-tation<br />Inference<br />Semantics<br />
  8. 8. Task of Inference<br />Inference<br />being able to derive new data<br />from data that you already know<br />dc:description<br />task<br />task<br />dc:description<br />Rule<br />Inference<br />TBox<br />Inference<br />Ontology<br />Inference<br />statements<br />that describe a system<br />in terms of controlled<br />vocabularies<br />task<br />dc:description<br />task<br />dc:description<br />ABox<br />Inference<br />TBox-compliant statements<br />about that vocabulary<br />to produce valid statements<br />within system<br />based on rule<br />
  9. 9. Ontology Inference<br />Ontology<br />Inference<br />to derive additional facts to be inferred<br />from instance data and class descriptions<br />based on own semantics<br />dc:description<br />RDF Semantics<br />Person<br />&lt;x, y&gt; is in IEXT(I(rdfs:subClassOf))<br />if and only if x and y are in IC<br />and ICEXT(x) is a subset of ICEXT(y)<br />Man<br />Myungjin<br />( Man rdfs:subClassOf Person )<br />( Myungjinrdf:type Man )<br />( Myungjinrdf:type Person )<br />
  10. 10. TBox Inference<br />TBox<br />Inference<br />Ontology<br />Inference<br />statements<br />that describe a system<br />in terms of controlled<br />vocabularies<br />dc:description<br />task<br />&lt;rdfs:Classrdf:about=&quot;http://xmlns.com/foaf/0.1/Document&quot; rdfs:label=&quot;Document”&gt;<br /> &lt;rdfs:subClassOfrdf:resource=&quot;http://xmlns.com/wordnet/1.6/Document&quot;/&gt;<br />&lt;/rdfs:Class&gt;<br />&lt;rdfs:Classrdf:about=&quot;http://xmlns.com/foaf/0.1/PersonalProfileDocument”&gt;<br /> &lt;rdfs:subClassOfrdf:resource=&quot;http://xmlns.com/foaf/0.1/Document&quot;/&gt;<br />&lt;/rdfs:Class&gt;<br />http://xmlns.com/foaf/0.1/PersonalProfileDocument<br />rdfs:subClassOf<br /> http://xmlns.com/wordnet/1.6/Document<br />
  11. 11. ABox Inference<br />Ontology<br />Inference<br />ABox<br />Inference<br />TBox-compliant statements<br />about that vocabulary<br />dc:description<br />task<br />&lt;rdf:Propertyrdf:about=&quot;http://xmlns.com/foaf/0.1/homepage” rdfs:label=&quot;homepage“ &gt;<br /> &lt;rdfs:subPropertyOfrdf:resource=&quot;http://xmlns.com/foaf/0.1/page&quot;/&gt;<br />&lt;/rdf:Property&gt;<br />&lt;foaf:Personrdf:about=&quot;#me&quot; xmlns:foaf=&quot;http://xmlns.com/foaf/0.1/&quot;&gt;<br /> &lt;foaf:name&gt;Dan Brickley&lt;/foaf:name&gt;<br /> &lt;foaf:homepagerdf:resource=&quot;http://danbri.org/&quot; /&gt;<br />&lt;/foaf:Person&gt;<br />http://xmlns.com/foaf/0.1 /#me foaf:page http://danbri.org/<br />
  12. 12. Rule Inference<br />Rule<br />Inference<br />to produce valid statements<br />within system<br />based on rule<br />dc:description<br />if hasParent(?x, ?y)<br />hasParent(?x, ?z)<br /> Man(?y)<br /> Woman(?z)<br />then hasWife(?y, ?z)<br />hasWife<br />hasParent<br />hasParent<br />
  13. 13. SWRL (Semantic Web Rule Language)<br />SWRL<br />Horn-like<br />Rule<br />Member<br />Submission<br />representation<br />status<br />editor<br />form<br />subLanguage<br />SWRLTab<br />RuleML<br />Body<br />rdf:Seq<br />rdf:li<br />rdf:li<br />Head<br />plugIn<br />Protégé<br />screenshot<br />
  14. 14. Inference Engine for Semantic Web<br />Bossam<br />a forward chaining rule engine supports SWRL<br />dc:description<br />rdf:type<br />Pellet<br />an open-source Java OWL DL reasoner has SWRL-support<br />dc:description<br />Inference<br />Engine<br />rdf:type<br />KAON2<br />an infrastructure for managing OWL-DL, SWRL, and F-Logic ontologies<br />dc:description<br />rdf:type<br />Racer<br />Pro<br />rdf:type<br />processing of rules in a SWRL-based syntax by translating them into nRQL rules<br />dc:description<br />rdf:type<br />Jena<br />to derive additional RDF assertions, the axioms and rules associated with the reasoner<br />dc:description<br />
  15. 15. SMART System<br />Intelligence<br />Information<br />System<br />Lab<br />Yonsei<br />University<br />java framework for semantic web application<br />locatedIn<br />created<br />dc:description<br />SMART<br />function<br />support<br />rdf:Bag<br />rdf:Bag<br />rdf:li<br />rdf:li<br />rdf:li<br />rdf:li<br />rdf:li<br />Ontology<br />Process<br />SPARQL<br />Process<br />rdf:li<br />SPARQL<br />RDF<br />RDFS<br />Rule<br />Inference<br />Ontology<br />Inference<br />SWRL<br />OWL<br />
  16. 16. Example Demo<br />SWRL Rule<br />if sioc:Post(?x)<br />sioc:Post(?y)<br />sioc:topic(?x, ?a)<br />sioc:topic(?y, ?b)<br />rdf:type(?a, ?z)<br />rdf:type(?b, ?z)<br />then sioc:related_to(?x, ?y)<br />sioc:Post<br />sioc:Post<br />rdf:type<br />rdf:type<br />sioc:related_to<br />clouds-with-sioc<br />sample-post<br />sioc:topic<br />sioc:topic<br />semantic-web<br />sws.geonames.org<br />SPARQL Query<br />PREFIX sioc: &lt;http://rdfs.org/sioc/ns#&gt;<br />SELECT ?u ?v <br />WHERE<br />{<br /> ?u sioc:related_to ?v .<br />}<br />rdf:type<br />rdf:type<br />semanticweb<br />
  17. 17. Issue of Inference<br />RDF 상에서 어디에 추론을 쓰지?<br />새로운 관계 발견을 통한 네트워크 분석<br />또 다른 RDF Vocabularies 혹은 도메인 온톨로지와의 관계 규칙 정의 및 추론<br />고민할 문제<br />추론을 위한 표현력과 복잡도<br />많은 룰에 의한 충돌<br />세상사를 반영한 규칙의 생성<br />철저한 준비?<br />표현력의 한계?<br />
  18. 18. ? !<br />

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