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Expressive Query Answering For Semantic Wikis

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Expressive Query Answering For Semantic Wikis

  1. 1. Expressive Query Answering For Semantic Wikis<br />Jie Bao, Rensselaer Polytechnic Institute<br />baojie@cs.rpi.edu, http://www.cs.rpi.edu/~baojie<br />
  2. 2. Outline<br />Background: Semantic MediaWiki<br />General Design Issues: Semantics and Expressivity<br />Formalizing SMW with Datalog<br />Extending SMW Modeling and Query Languages<br />Implementations and Experimental Results<br />Jan 18, 2011<br />2<br />
  3. 3. Semantic Wiki as a Data Store<br />Jan 18, 2011<br />3<br />
  4. 4. Semantic MediaWiki (SMW)<br />4<br />It is the most popular semantic wiki system extending MediaWiki<br />Mediawiki: What you edit<br />what you see<br />Jan 18, 2011<br />
  5. 5. Semantic MediaWiki<br />5<br />To author knowledge<br />typed link (property)<br />SMW: What you edit<br />(Modeling Language)<br />what you see<br />Jan 18, 2011<br />
  6. 6. Semantic MediaWiki<br />6<br />To retrieve knowledge<br />SMW: What you edit<br />(Querying Language)<br />what you see<br />Jan 18, 2011<br />
  7. 7. Why SMW?<br />Low-cost solution for light-weight semantic applications<br />Integrated environment for modeling and querying<br />Simple to setup, easy to use<br />Can work with hundreds of other MW/SMW extensions<br />Templating, Visualization, Editing, I/O, Workflow… <br />Access Control, Forms, Maps, SPARQL…<br />Jan 18, 2011<br />7<br />
  8. 8. Expressivity (SMW 1.5.4)<br />SMW-ML (Modeling Language)<br />category instantiation e.g., [[Category:C]]<br />property instantiation e.g., [[P::v]]<br />subclass, e.g., [[Category:C]] (on a category page)<br />subproperty, e.g., [[Subpropetyof:Property:P]] (on a property page)<br />SMW-QL (Query Language)<br />conjunction: e.g., [[Category:C]][[P::v]]<br />disjunction: e.g., [[Category:C]] or [[P::v]], [[A||B]] or [[P::v||w]]<br />property chain: e.g., [[P.Q::v]]<br />property wildcat: e.g., [[P::+]]<br />subquery: e.g., [[P::<q>[[Category:C]]</q>]]<br />inverse property e.g., [[-P::v]]<br />value comparison, e.g. [[P::>3]][[P::<7]][[P::!5]]<br />Jan 18, 2011<br />8<br />
  9. 9. However, we often need more expressivity<br />Modeling<br />Domain and Range: “has author” is from “person” to “document”<br />Inverse property: “has author” <-> “author of”<br />Transitive property: “part of”<br />…<br />Query<br />Negation: find cities that are not capitals<br />Counting: find professors who advise more than 5 students<br />Jan 18, 2011<br />9<br />
  10. 10. Extending SMW<br />Goal: offer additional expressivity without losing “wikiness” (i.e., collaborative, simple, easy to learn, informality-tolerate, and evolving-capable )<br />Jan 18, 2011<br />10<br />
  11. 11. Design Issues: Semantics and Expressivity<br />Jan 18, 2011<br />11<br />
  12. 12. Design Issue 1: Open or Close world?<br />OWL/DL -Like DB/Rule-Like <br />Jan 18, 2011<br />12<br />or<br />
  13. 13. Design Issue 2: Expressivity Supported<br />A subset of OWL that <br />Can be implemented using rules<br />Is syntactically simple for common wiki users<br />Why not full OWL 2 RL or OWL 2 QL?<br />Too complicated for most wiki users<br />Jan 18, 2011<br />13<br />
  14. 14. Design Issue 3: Implementation<br />Reuse existing tools if we can<br />Low learning curve: hide details from users; incremental changes from SMW<br />Portability: allow users to choose different backend stores (MySQL, SQL Server, etc.)<br />Fast enough for a typical semantic wiki (has < O(104) pages [1])<br />Jan 18, 2011<br />14<br />[1] http://semantic-mediawiki.org/wiki/Sites_using_Semantic_MediaWiki<br />
  15. 15. Solution<br />Formalizing SMW modeling and query languages using datalog<br />Descriptive, closed-world semantics<br />Well-understood complexity and many known optimizations<br />Implementation: <br />leverage highly-optimized LP solvers for reasoning, e.g., DLV, Clasp, and Smodels<br />Reuse SMW UI for rendering query results<br />Jan 18, 2011<br />15<br />
  16. 16. Expressivity<br />Modeling Language: a subset of OWL Prime (or RDFS++ named by others)<br />rdfs:subClassOf, subPropertyOf, domain, range<br />owl:TransitiveProperty, SymmetricProperty, FunctionalProperty,<br />InverseFunctionalProperty, inverseOf<br />owl:sameAs, equivalentClass, equivalentProperty<br />Query Language: SMW-QL, plus<br />Negation as failure<br />Cardinality<br />Jan 18, 2011<br />16<br />
  17. 17. Modeling SMW with datalog<br />Jan 18, 2011<br />17<br />
  18. 18. Translation Rules for SMW-ML<br />Subproperty<br />Subclass<br />Class instance<br />Property instance<br />Redirection<br />P(x,y) :- Q(x,y) .<br />C(x) :- D(x) .<br />C(a) .<br />P(a,b) .<br />a=b.<br />Jan 18, 2011<br />18<br />
  19. 19. Translation Rules for SMW-QL<br />{{#ask:<br /> [[Category:City]]<br /> [[capital of::+]] <br />}}<br />result(x) :- City(x), capital_of(x, y) .<br />Jan 18, 2011<br />19<br />
  20. 20. Translation Rules for SMW-QL<br />result(x) :- _tmp0(x).<br />_tmp0(x) :- A(x), p3(x,x0), x0=category:B.<br />_tmp0(x) :- p(x,x2), p1(x2,x3), p2(x3,x1), _tmp9(x1).<br />_tmp9(x1) :- _tmp12(x1).<br />_tmp12(x1) :- D(x1).<br />_tmp12(x1) :- p1(x1,x4), x4=SomePage.<br />_tmp9(x1) :- thing(x), x !=v.<br />_tmp9(x1) :- E(x1).<br />{{#ask: [[Category:A]][[p3::category:B]] or <br /> [[p.p1.p2::<br /><q><br /> [[Category:D]] or [[p1::<q>[[SomePage]]</q>]]<br /> </q><br />||!v<br />||<q>[[Category:E]]</q><br /> ]]<br />}}<br />Conjunction<br />Property chain<br />Disjunction<br />Inequality<br />Subquery<br />Jan 18, 2011<br />20<br />
  21. 21. Extending SMW-ML and SMW-QL<br />Jan 18, 2011<br />21<br />
  22. 22. SMW-ML+<br />[[Domain::C]]<br />[[Range::C]]<br />[[Type::Transitive]]<br />[[Type::Symmetric]]<br />[[Type::Functional]]<br />[[Type::InverseFunctional]]<br />[[Inverse of::Q]]<br />C(x) :- P(x,y)<br />C(y) :- P(x,y)<br />P(x,y) :- P(x,z), P(z,y)<br />P(x,y) :- P(y,x)<br />SameAs(x,y) :- P(z,x),P(z,y)<br />SameAs(x,y) :- P(x,z),P(y,z)<br />Q(x,y) :- P(y,x)<br />Jan 18, 2011<br />22<br />On page “Property:P”<br />
  23. 23. SMW-QL+ : Negations<br />{{#askplus:<br /> [[<>Category:C]]<br /> [[Category:D]]<br />}}<br />{{#askplus:<br /> [[Category:C]]<br /> [[<>P::+]]<br />}}<br />result(x) :- D(x), not C(x) .<br />result(x) :- C(x), #count{x: P(x,y)}<=0 .<br />Jan 18, 2011<br />23<br />
  24. 24. SMW-QL+: (Non)qualified Cardinality<br />{{#askplus:<br /> [[>=3#P::+]]<br />}}<br />{{#askplus:<br /> [[>=3#P::<br /> <q>[[Category:D]]</q>]]<br />}}<br />result(x) :- thing(x),<br /> #count{x: P(x,y)}>=3 .<br />result(x) :- thing(x),<br /> #count{x: P(x,y),D(y)}>=3 .<br />Jan 18, 2011<br />24<br />For safeness<br />
  25. 25. Theoretical Complexity<br />Jan 18, 2011<br />25<br />Recall that L  NL  P  NP<br />
  26. 26. Implementation and Experimental Results<br />Jan 18, 2011<br />26<br />
  27. 27. Implementation<br />Using DLV as the reasoner<br />Other LP solvers may be used as well<br />Two work modes<br /> File-based: reasoning based on a static dump (snapshot) of wiki semantic data.<br /> Database-based:  reasoning based on a shadow database via ODBC; Real-time changes of instance data will be updated.<br />Optimization<br />Caching<br />Jan 18, 2011<br />27<br />
  28. 28. Example:<br />Jan 18, 2011<br />28<br />Inverse property<br />Caching<br />Transitive property<br />
  29. 29. Scalability: Data Complexity<br />Test machine: 2 * Xeon 5365 Quad 3.0GHz 1333MHz /16G / 2 * 1TB<br />Dataset: part of DBLP, 10,396 pages, 100,736 triples<br />Jan 18, 2011<br />29<br />{{#askplus: [[Category:Person]] }}<br />Near linear <br />
  30. 30. Scalability: Query Complexity<br />Jan 18, 2011<br />30<br />{{#askplus: [[Knows::<q>[[Knows::<q>[[Knows::<q>…</q>]]</q>]]</q>]] }}<br />Near constant<br /><ul><li>Dataset: DBLP 100k triples</li></li></ul><li>Scalability: Query Complexity<br />Jan 18, 2011<br />31<br />{{#askplus: [[Knows::+]] or [[Knows::+]] or [[Knows::+]] …}}<br />Near constant<br /><ul><li>Dataset: DBLP 100k triples</li></li></ul><li>The SemanticQueryRDFS++ extension<br />Jan 18, 2011<br />32<br />http://www.mediawiki.org/wiki/Extension:SemanticQueryRDFS++<br />
  31. 31. Conclusions and Future Work<br />Formalizing SMW using datalog allows us to<br />analyze the reasoning complexity of SMW<br />extend SMW modeling and query languages for an expressive subset of OWL<br />implement a SMW query engine based on DLV that is scalable for typical uses.<br />Future Work<br />Incremental reasoning<br />Customized reasoning rules<br />SPARQL <-> SMW-QL+ translations<br />Jan 18, 2011<br />33<br />

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