Semantic Coordination: A New Approach and an Application

Semantic coordination, namely the problem of finding an agreement on the meaning of heterogeneous semantic models, is one of the key issues in the development of the Semantic Web. In this paper, we propose a new algorithm for discovering semantic mappings across hierarchical classifications based on a new approach to semantic coordination. This approach shifts the problem of semantic coordination from the problem of computing linguistic or structural similarities (what most other proposed approaches do) to the problem of deducing relations between sets of logical formulae that represent the meaning of concepts belonging to different models. We show how to apply the approach and the algorithm to an interesting family of semantic models, namely hierarchical classifications, and present the results of preliminary tests on two types of hierarchical classifications, web directories and catalogs. Finally, we argue why this is a significant improvement on previous approaches.

[1]  Kaizhong Zhang,et al.  On the Editing Distance between Undirected Acyclic Graphs and Related Problems , 1995, CPM.

[2]  Paolo Bouquet,et al.  KEEx: A Peer-to-Peer Solution for Distributed Knowledge Management , 2002, P2PKM.

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

[4]  Tova Milo,et al.  Using Schema Matching to Simplify Heterogeneous Data Translation , 1998, VLDB.

[5]  Zahir Tari,et al.  On the Move to Meaningful Internet Systems 2002: CoopIS, DOA, and ODBASE , 2002, Lecture Notes in Computer Science.

[6]  J. Overhage,et al.  Sorting Things Out: Classification and Its Consequences , 2001, Annals of Internal Medicine.

[7]  Kaleem Siddiqi,et al.  Matching Hierarchical Structures Using Association Graphs , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  George Lakoff,et al.  Women, Fire, and Dangerous Things , 1987 .

[9]  Paolo Avesani Evaluation Framework for Local Ontologies Interoperability , 2002 .

[10]  Bernd Neumann,et al.  Computer Vision — ECCV’98 , 1998, Lecture Notes in Computer Science.

[11]  James A. Hendler,et al.  The Semantic Web — ISWC 2002 , 2002, Lecture Notes in Computer Science.

[12]  Fausto Giunchiglia,et al.  Local Models Semantics, or Contextual Reasoning = Locality + Compatibility , 1998, KR.

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

[14]  Samuel T. Waters,et al.  American Association for Artificial Intelligence (AAAI) , 1988 .

[15]  Silvana Castano,et al.  Semantic integration of semistructured and structured data sources , 1999, SGMD.

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

[17]  Kaizhong Zhang,et al.  A System for Approximate Tree Matching , 1994, IEEE Trans. Knowl. Data Eng..

[18]  M. Bonifacio,et al.  Enabling Distributed Knowledge Management: Managerial and Technological Implications , 2002 .

[19]  Jeremy J. Carroll,et al.  Matching RDF Graphs , 2002, SEMWEB.

[20]  David S. Day,et al.  Phrase Parsing with Rule Sequence Processors: an Application to the Shared CoNLL Task , 2000, CoNLL/LLL.

[21]  Alexander Borgida,et al.  Distributed Description Logics: Directed Domain Correspondences in Federated Information Sources , 2002, OTM.

[22]  John G. Hughes,et al.  Semantic Information Mediation among Multiple Product Ontologies , 1999 .