Ontology Mapping: An Information Retrieval and Interactive Activation Network Based Approach

Ontology mapping is to find semantic correspondences between similar elements of different ontologies. It is critical to achieve semantic interoperability in the WWW. This paper proposes a new generic and scalable ontology mapping approach based on propagation theory, information retrieval technique and artificial intelligence model. The approach utilizes both linguistic and structural information, measures the similarity of different elements of ontologies in a vector space model, and deals with constraints using the interactive activation network. The results of pilot study, the PRIOR, are promising and scalable.

[1]  Marc Ehrig,et al.  State of the art on ontology alignment , 2013 .

[2]  Ya N N I S K A L F O G L O U,et al.  Ontology mapping: the state of the art* , 2003 .

[3]  Ming Mao,et al.  A Profile Propagation and Information Retrieval Based Ontology Mapping Approach , 2007 .

[4]  John Domingue,et al.  Artificial Intelligence: Methodology, Systems, and Applications, 12th International Conference, AIMSA 2006, Varna, Bulgaria, September 12-15, 2006, Proceedings , 2006, AIMSA.

[5]  Erhard Rahm,et al.  Similarity flooding: a versatile graph matching algorithm and its application to schema matching , 2002, Proceedings 18th International Conference on Data Engineering.

[6]  Peishen Qi,et al.  Ontology Translation on the Semantic Web , 2003, J. Data Semant..

[7]  Ming Mao,et al.  A Profile Propagation and Information Retrieval Based Ontology Mapping Approach , 2007, Third International Conference on Semantics, Knowledge and Grid (SKG 2007).

[8]  Edward P. K. Tsang,et al.  Foundations of constraint satisfaction , 1993, Computation in cognitive science.

[9]  Ming Mao,et al.  PRIOR System: Results for OAEI 2006 , 2006, Ontology Matching.

[10]  Jérôme Euzenat,et al.  An API for Ontology Alignment , 2004, SEMWEB.

[11]  Pedro M. Domingos,et al.  Learning to match ontologies on the Semantic Web , 2003, The VLDB Journal.

[12]  Marek Hatala,et al.  Ontology mappings to improve learning resource search , 2006, Br. J. Educ. Technol..

[13]  Natalya F. Noy,et al.  Semantic integration: a survey of ontology-based approaches , 2004, SGMD.

[14]  Dean Allemang,et al.  The Semantic Web - ISWC 2006, 5th International Semantic Web Conference, ISWC 2006, Athens, GA, USA, November 5-9, 2006, Proceedings , 2006, SEMWEB.

[15]  Heiner Stuckenschmidt,et al.  Results of the Ontology Alignment Evaluation Initiative , 2007 .

[16]  James L. McClelland,et al.  Explorations in parallel distributed processing: a handbook of models, programs, and exercises , 1988 .

[17]  Yannis Kalfoglou,et al.  Ontology mapping: the state of the art , 2003, The Knowledge Engineering Review.

[18]  Daniel P. Huttenlocher,et al.  Efficient Belief Propagation for Early Vision , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[19]  Eduard Hovy,et al.  Combining and standardizing large- scale, practical ontologies for machine tranlation and other uses , 1998, LREC.

[20]  Heiner Stuckenschmidt,et al.  Results of the Ontology Alignment Evaluation Initiative 2007 , 2006, OM.

[21]  Yuzhong Qu,et al.  Constructing virtual documents for ontology matching , 2006, WWW '06.

[22]  Marc Ehrig Ontology Alignment: Bridging the Semantic Gap (Semantic Web and Beyond) , 2006 .