Semantic Matching of Natural Language Web Queries

In this paper, we propose a method to automatically rank documents returned by a search engine in the WWW with respect to a query. The process consists in three steps, the first translates the query and document descriptions into description logic terminologies. The second computes a mapping between related elements in the query and each document. This mapping matches concepts in the terminologies based on their names and their definitions. The last step computes the difference between the query (represented as a terminology) and each document (also represented as a terminology) and ranks the documents according this difference. To deal with linguistic information when comparing description logic concepts, we propose a definition of subsumption that takes into account names similarity between concepts occurring in the descriptions being compared. We describe each step of the method and show the intended results on a running example.

[1]  Renate A. Schmidt,et al.  Terminological Representation, Natural Language & Relation Algebra , 1992, GWAI.

[2]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[3]  Pedro M. Domingos,et al.  Learning to map between ontologies on the semantic web , 2002, WWW '02.

[4]  Bijan Parsia,et al.  Task Computing - The Semantic Web Meets Pervasive Computing , 2003, SEMWEB.

[5]  Steffen Staab,et al.  SEAL - A Framework for Developing SEmantic Web PortALs , 2001, BNCOD.

[6]  Michel Schneider,et al.  Comparing Natural Language Documents: a DL Based Approach , 2003, Description Logics.

[7]  Ralf Küsters,et al.  Computing Least Common Subsumers in Description Logics with Existential Restrictions , 1999, IJCAI.

[8]  Ralf Küsters.  Non-Standard Inferences in Description Logics , 2001, Lecture Notes in Computer Science.

[9]  James A. Hendler,et al.  The Semantic Web: A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities , 2001 .

[10]  Graeme Hirst,et al.  Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures , 2004 .

[11]  Erhard Rahm,et al.  Generic Schema Matching with Cupid , 2001, VLDB.

[12]  Steffen Staab,et al.  Measuring Similarity between Ontologies , 2002, EKAW.

[13]  Gilles Bisson,et al.  Learning in FOL with a Similarity Measure , 1992, AAAI.

[14]  Graeme Hirst,et al.  Lexical chains as representations of context for the detection and correction of malapropisms , 1995 .

[15]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[16]  Koichi Takeda,et al.  Information retrieval on the web , 2000, CSUR.

[17]  Takahiro Kawamura,et al.  Delivering Semantic Web Services , 2003, WWW.

[18]  Gunnar Teege.  Making the Difference: A Subtraction Operation for Description Logics , 1994, KR.

[19]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.