Detecting Semantic Relations Between Nominals Using Support Vector Machines and Linguistic-Based Rules

  • Isabel Segura-Bedmar
  • Doaa Samy
  • Jose L. Martínez-Fernández
  • Paloma Martínez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4806)

Abstract

This paper describes the improvement of an automatic system for detecting semantic relations between nominals by the use of linguistically motivated knowledge combined with machine learning techniques. A previous version of the system using a Support Vector Machine classifier was evaluated in the 4th International Workshop on Semantic Evaluations, SEMEVAL [5]. The performance of the system improved significantly by the application of the linguistic based rules.

Keywords

computational semantics semantic relations classification Support Vector Machines Sequential Minimal Optimization 

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References

  1. 1.
    Kietz, J.U., Maedche, A., Volz, R.: A method for semi-automatic ontology acquisiton from a corporare Intranet. In: Dieng, R., Corby, O. (eds.) EKAW 2000. LNCS (LNAI), vol. 1937, pp. 1–4. Springer, Heidelberg (2000)Google Scholar
  2. 2.
    Lee, D., CHU, W.W.: Constraints-Preserving Transformation from XML Document Type Definition to Relational Schema. In: Laender, A.H.F., Liddle, S.W., Storey, V.C. (eds.) ER 2000. LNCS, vol. 1920, Springer, Heidelberg (2000)Google Scholar
  3. 3.
    Maedche, A., Staab, S.: Measuring similarity between ontologies. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, Springer, Heidelberg (2002)Google Scholar
  4. 4.
    Platt, J. Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector MachinesMicrosoft Research Technical Report MSR-TR-98-14 (1998)Google Scholar
  5. 5.
    Segura Bedmar, I., Samy, D., Martinez-Fernández, J.L.: UC3M: Classification of Semantic Relations between Nominals using Sequential Minimal Optimization. In: Proc. of SEMEVAL, ACL O7. Prague (2007)Google Scholar
  6. 6.
    Specia, L., Motta, E.: A hybrid approach for extracting semantic relations from texts. In: 2nd Workshop on Ontology Learning and Population (2006)Google Scholar
  7. 7.
    Witten, H., Frank, E.: Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann, San Francisco (2005)MATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Isabel Segura-Bedmar
    • 1
  • Doaa Samy
    • 1
  • Jose L. Martínez-Fernández
    • 1
  • Paloma Martínez
    • 1
  1. 1.Universidad Carlos III de Madrid, Computer Science Departament, Avd. Universidad, 30, Leganes, 28911, MadridSpain

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