Skip to main content
SpringerLink
Log in

Combination of Lexical and Structure-Based Similarity Measures to Match Ontologies Automatically

  • Conference paper
Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 415))

Abstract

The great development of semantic web in the distributed environment leads to the different forms of ontologies. Therefore, ontology matching is an important task in order to share knowledge among applications more easily. In this paper, we propose an automatic ontology matching method by combining lexical and structure-based measures. A basic lexical similarity measure is applied to all pairs of concepts of two ontologies to achieve an initial matrix. With this matrix, we calculate the similarity between concepts based on a new structural similarity measure. Additionally, the structure-based matching method is improved by using a set of centroid concepts to reduce the computation time. We use I 3 CON 2004 benchmark to evaluate the proposed method. The experimental results show that our measure has some prominent features for ontology matching.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Akbari, I., Fathian, M., Badie, K.: An Improved MLMA+ Algorithm and its Application in Ontology Matching. In: Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA), pp. 56–60. IEEE Xplore (2009)

    Google Scholar 

  2. Akbari, I., Fathian, M.: A Novel Algorithm for Ontology Matching. Journal of Information Science 36(3), 324–334 (2010)

    Article  Google Scholar 

  3. Alasoud, A., Haarslev, V., Shiri, N.: An Empirical Comparison of Ontology Matching Techniques. Journal of Information Science 35(4), 379–397 (2009)

    Article  Google Scholar 

  4. Do, H.H., Rahm, E.: COMA - A System for Flexible Combination of Schema Matching Approaches. In: 28th International Conference on Very Large Data Bases, pp. 610–621. ACM (2002)

    Google Scholar 

  5. Dong, X., Madhavan, J., Halevy, A.Y.: Mining Structures for Semantics. SIGKDD Explorations Newsletter 6(2), 53–60 (2004)

    Article  Google Scholar 

  6. Eidoon, Z., Yazdani, N., Oroumchian, F.: A Vector based Method of Ontology Matching. In: 3rd International Conference on Semantics, Knowledge and Grid (SKG), pp. 378–381. IEEE Xplore (2007)

    Google Scholar 

  7. Euzenat, J., Shvaiko, P.: Ontology Matching. Springer, Leipzig (2007)

    MATH  Google Scholar 

  8. Euzenat, J., Valtchev, P.: Similarity-Based Ontology Alignment in OWL-Lite. In: European Conference on Artificial Intelligence (ECAI), pp. 333–337. IOS Press (2004)

    Google Scholar 

  9. Hanif Seddiqui, M., Aono, M.: An Efficient and Scalable Algorithm for Segmented Alignment of Ontologies of Arbitrary Size. Journal of Web Semantics: Science, Services and Agents on the World Wide Web, 344–356 (2009)

    Google Scholar 

  10. Hughes, T., Ashpole, B.: Information Interpretation and Integration Conference (2004), http://www.atl.external.lmco.com/projects/ontology/i3con.html

  11. Jean-Mary, Y.R., et al.: Ontology Matching with Semantic Verification. Journal on Web Semantics: Science, Services and Agents on the World Wide Web 7(3), 235–251 (2009)

    Article  Google Scholar 

  12. Levenshtein, V.I.: Binary Codes Capable of Correcting Deletions, Insertions, and Reversals. Soviet Physics Doklady 10, 707–710 (1966)

    MathSciNet  Google Scholar 

  13. Madhavan, J., Bernstein, P., Rahm, E.: Generic Schema Matching with Cupid. In: 27th International Conference on Very Large Data Bases, pp. 49–58. Morgan Kaufmann, San Francisco (2001)

    Google Scholar 

  14. Maedche, A., Staab, S.: Measuring Similarity between Ontologies. In: 13th International Conference on Knowledge Engineering and Knowledge Management: Ontologies and the Semantic Web, pp. 251–263. Springer, London (2002)

    Chapter  Google Scholar 

  15. Melnik, S., Garcia-Molina, H., Rahm, E.: Similarity Flooding: A Versatile Graph Matching Algorithm and its Application to Schema Matching. In: 18th International Conference on Data Engineering (ICDE), pp. 117–128. IEEE Xplore (2002)

    Google Scholar 

  16. Miller, G.A.: WordNet: A Lexical Database for English. Communications of the ACM 38, 39–41 (1995)

    Article  Google Scholar 

  17. Nguyen, T.T.A., Conrad, S.: A New Structure-based Similarity Measure for Automatic Ontology Matching. In: 4th International Conference on Knowledge Discovery and Information Retrieval, pp. 443–449. SciTePress (2012)

    Google Scholar 

  18. Noy, N.F., Musen, M.A.: Anchor-PROMPT: Using Non-local Context for Semantic Matching. In: Workshop on Ontologies and Information Sharing at the 17th International Joint Conference on Artificial Intelligence, IJCAI (2001)

    Google Scholar 

  19. Prashant, D., Ravikanth, K., Christopher, T.: Inexact Matching of Ontology Graphs Using Expectation-Maximization. Journal on Web Semantics: Science, Services and Agents on the World Wide Web 7(2), 90–106 (2009)

    Article  Google Scholar 

  20. Sharma, A.: Ontology Matching Using Weighted Graphs. In: 1st International Conference on Digital Information Management (ICDIM), pp. 121–124. IEEE Xplore (2006)

    Google Scholar 

  21. Shvaiko, P., Euzenat, J.: A Survey of Schema-Based Matching Approaches. In: Spaccapietra, S. (ed.) Journal on Data Semantics IV. LNCS, vol. 3730, pp. 146–171. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  22. Sunna, W., Cruz, I.F.: Structure-Based Methods to Enhance Geospatial Ontology Alignment. In: Fonseca, F., Rodríguez, M.A., Levashkin, S. (eds.) GeoS 2007. LNCS, vol. 4853, pp. 82–97. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  23. Tang, J., Li, J., Liang, B., Huang, X., Li, Y., Wang, K.: Using Bayesian Decision for Ontology Mapping. Journal on Web Semantics: Science, Services and Agents on the World Wide Web 4(4), 243–262 (2006)

    Article  Google Scholar 

  24. Wang, Y., Liu, W., Bell, D.A.: A Structure-Based Similarity Spreading Approach for Ontology Matching. In: Deshpande, A., Hunter, A. (eds.) SUM 2010. LNCS, vol. 6379, pp. 361–374. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Computer Science, Heinrich-Heine-University Düsseldorf, Universitätsstr. 1, D-40225, Düsseldorf, Germany

    Thi Thuy Anh Nguyen & Stefan Conrad

Authors
  1. Thi Thuy Anh Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stefan Conrad
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. IST - Technical University of Lisbon, Av.Rovisco Pais, 1, 1049-001, Lisbon, Portugal

    Ana Fred

  2. Delft University of Technology, Mekelweg 4, 2628, Delft, CD, The Netherlands

    Jan L. G. Dietz

  3. Informatics Research Centre, Henley Business School, University of Reading, RG6 6UD, UK

    Kecheng Liu

  4. INSTICC and IPS, Estefanilha, Setúbal, Portugal

    Joaquim Filipe

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Nguyen, T.T.A., Conrad, S. (2013). Combination of Lexical and Structure-Based Similarity Measures to Match Ontologies Automatically. In: Fred, A., Dietz, J.L.G., Liu, K., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2012. Communications in Computer and Information Science, vol 415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54105-6_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-54105-6_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54104-9

  • Online ISBN: 978-3-642-54105-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation