Opening the Black Box of Ontology Matching

Due to the high heterogeneity of ontologies, a combination of many methods is necessary in order to discover correctly the semantic correspondences between their elements. An ontology matching tool can be seen as a collection of several matching components, each implementing a specific method dealing with a specific heterogeneity type (terminological, structural or semantic). In addition, a mapping selection module is introduced to filter out the most likely mapping candidates. This paper proposes an empirical study of the interaction between these components working together inside an ontology matching system. By the help of datasets from the Ontology Alignment Evaluation Initiative, we have carried out several experimental studies. In the first place, we have been interested in the impact of the mapping selection module on the performance of terminological and structural matchers revealing the advantage of using global methods vs. local ones. Further, we have carried an extensive study on the flaw of the performance of a structural matcher in the presence of noisy input coming from a terminological method. Finally, we have analyzed the behavior of a structural and a semantic component with respect to inputs taken from different terminological matchers.

[1]  A. Tversky Features of Similarity , 1977 .

[2]  David W. Conrath,et al.  Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy , 1997, ROCLING/IJCLCLP.

[3]  Rose Dieng,et al.  Comparison of Personal Ontologies Represented through Conceptual Graphs , 1998, ECAI.

[4]  Dekang Lin,et al.  An Information-Theoretic Definition of Similarity , 1998, ICML.

[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]  Fausto Giunchiglia,et al.  S-Match: an Algorithm and an Implementation of Semantic Matching , 2004, ESWS.

[7]  Fabien L. Gandon,et al.  On Ontology Matching Problems , 2004 .

[8]  Enrico Motta,et al.  The Semantic Web - ISWC 2005, 4th International Semantic Web Conference, ISWC 2005, Galway, Ireland, November 6-10, 2005, Proceedings , 2005, SEMWEB.

[9]  Yuzhong Qu,et al.  FalconAO: Aligning Ontologies with Falcon , 2005, Integrating Ontologies.

[10]  Stefanos D. Kollias,et al.  A String Metric for Ontology Alignment , 2005, SEMWEB.

[11]  Heiner Stuckenschmidt,et al.  Analyzing Mapping Extraction Approaches , 2007, OM.

[12]  Isabel F. Cruz,et al.  Structure-Based Methods to Enhance Geospatial Ontology Alignment , 2007, GeoS.

[13]  Michael B. Spring,et al.  A Harmony based Adaptive Ontology Mapping Approach , 2008, SWWS.

[14]  Baowen Xu,et al.  Lily: Ontology Alignment Results for OAEI 2008 , 2008, OM.

[15]  Lora Aroyo,et al.  The Semantic Web: Research and Applications , 2009, Lecture Notes in Computer Science.

[16]  Mansur R. Kabuka,et al.  Ontology matching with semantic verification , 2009, J. Web Semant..

[17]  Cosmin Stroe,et al.  Using AgreementMaker to align ontologies for OAEI 2010 , 2010, OM.

[18]  Tharam S. Dillon,et al.  On the Move to Meaningful Internet Systems, OTM 2010 , 2010, Lecture Notes in Computer Science.

[19]  Christian Meilicke,et al.  Alignment incoherence in ontology matching , 2011 .

[20]  Selmin Nurcan IS Olympics: Information Systems in a Diverse World , 2011, Lecture Notes in Business Information Processing.

[21]  Bernardo Cuenca Grau,et al.  LogMap: Logic-Based and Scalable Ontology Matching , 2011, SEMWEB.

[22]  Lora Aroyo,et al.  The Semantic Web - ISWC 2011 - 10th International Semantic Web Conference, Bonn, Germany, October 23-27, 2011, Proceedings, Part I , 2011, SEMWEB.

[23]  Zohra Bellahsene,et al.  A Flexible System for Ontology Matching , 2011, CAiSE Forum.

[24]  Zohra Bellahsene,et al.  A Generic Approach for Combining Linguistic and Context Profile Metrics in Ontology Matching , 2011, OTM Conferences.

[25]  Jan Nößner,et al.  CODI: Combinatorial Optimization for Data Integration: results for OAEI 2011 , 2010, OM.

[26]  Duy-Hoa Ngo,et al.  Enhancing Ontology Matching by Using Machine Learning, Graph Matching and Information Retrieval Techniques. (Amélioration de l'alignement d'ontologies par les techniques d'apprentissage automatique, d'appariement de graphes et de recherche d'information) , 2012 .

[27]  Jérôme Euzenat,et al.  Ontology Matching: State of the Art and Future Challenges , 2013, IEEE Transactions on Knowledge and Data Engineering.

[28]  J. Euzenat,et al.  Ontology Matching , 2007, Springer Berlin Heidelberg.