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A Hybrid Layered Approach for Ontology Matching


  • School of Computing, SASTRA University, Thanjavur - 613401, Tamil Nadu, India


Ontologies act as a key technology for the visualization of the semantic web and their existence in different domains produces a heterogeneity problem for information integration. The process of ontology matching solves the heterogeneity problem by identifying the semantically related identical entities available from different ontologies. Finding similarity between the class names across the input ontologies is the major step performed in every ontology matching process. Most of the existing methods compare the class names only based on their similarity irrespective of their real meaning. This paper suggests a hybrid layered approach for matching the ontology classes. This approach calculates syntactic, semantic and structural similarity between the classes from input ontologies in successive layers. Finally, the alignment layer generates the final matching results by combining the results obtained from the previous layers and generates semantic mappings between them. This approach can also be applied to match other entities of the ontology. The results obtained prove that the proposed approach overtakes the other existing methods, thereby improving the accuracy of the results achieved.


Ontology matching;Synset;Semantic relations;Ontology classes.

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  • Hassanzadeh O, Lim L, Kementsietsidis A, Wang M. A declarative framework for semantic link discovery over relational data. In Proceedings of the 18thInternational Conference on World Wide Web (WWW ’09); p.1101–1102.
  • Kalfoglou Y, Schorlemmer M. Ontology mapping: the state of the art. The Knowledge Engineering Review 18; p. 1–31;(2003).
  • Pavel S, Euzenat J. Ontology matching: state of the art and future challenges. IEEE Transactions on Knowledge and Data Engineering; (2011).
  • Doan A, Madhavan J, Dhamankar R, Domingos P, Halevy A. Learning to
  • match ontologies on the semantic web. The VLDB Journal 12;p.303–319; (2003).
  • Choi N, Song I Y, Han H.A survey on ontology mapping. ACM SIGMOD Record 35; p.34–41; (2006).
  • Li J, Tang J, Li Y, Luo Q. Rimom: a dynamic multistrategy ontology alignment framework. IEEE Transactions on Knowledge and Data Engineering 21;p.1218–1232; (2009).
  • Cruz I F, Antonelli F P, & Stroe C. AgreementMaker: Efficient matching for large real-world schemas and ontologies. In Proc. VLDB Endow. 2 (pp. 1586– 1589); August 2009.
  • Do H H, Rahm E. Coma: a system for flexible combination of schema
  • matching approaches. In: Proceedings of the 28th International Conference on
  • Very Large Data Bases (VLDB ’02); pp. 610–621.
  • Yves R. Jean-Mary,Patrick Shironoshita E and Mansur R. Kabuka.Ontology matching with semantic verification. Journal of Web Semantics, Article in Press, Elsevier; 2009.
  • Aumueller D,Do S, Massmann H H, and Rahm E. Schema and ontology
  • matching with coma++. In SIGMOD;2005.
  • Hu W, Qu Y. Falcon-AO: a practical ontology matching system. Web Semantics: Science, Services and Agents on the World Wide Web 6 ;p. 237–239; 2008.
  • Giunchiglia, F, Shvaiko P, and Yatskevich M. S-Match: An algorithm and implementation of semantic matching. In Proceedings of the European Semantic Web Symposium, LNCS 3053; pp.61-75;2004.
  • Alalwan N. Zedan H, and Siewe F. Generating OWL Ontology for Database Intgeration.In proceedings of Third International Conference on Advance in Semantic Processing;pp.22-31;2009.
  • Bunke H, Csirik J.Parametric String Edit Distance and Its Application to Pattern Recognition. IEEE Transactions on Systems, Man, and Cybernetics, vol. 25;pp. 202-206; 1995.
  • Cohen W.W, Ravikumar P, and Fienberg S.E.A Comparison of String Distance Metrics for Name-Matching Tasks. In Proceedings of II Web; pp.73-78;2003.
  • Yuzhong Qu, Wei Hu, Gong Cheng. Constructing Virtual Documents for Ontology Matching.Wide Web 4;p. 243–262;2006.
  • Salton G, Yang C S. On the specification of term values in automatic indexing. Journal of Documentation 29 (1973); 351–372.
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