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Automatic Ontology Extraction from Heterogeneous Documents for E-Learning Applications

  • J. Jeslin Shanthamalar
  • C. R. Rene Robin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 243)

Abstract

In this paper, we present our approach to build domain ontology for e-learning purposes from heterogeneous documents by using the automatic extraction technique. Ontologies have been frequently employed in order to solve problems for shared distributed knowledge and the effective integration of information across many applications. The process of ontology building is a very lengthy and error-prone work. Therefore, a number of research studies to build ontologies semi-automatically from existing documents have been developed. This paper proposes a novel method which is used to build ontology, using the existing knowledge base of heterogeneous documents for complex application domains without the need of human intervention. This method improves the system performance and accuracy and reduces the time for the ontology building process from a collection of documents.

Keywords

E-learning Information extraction Automatic extraction Domain ontology 

References

  1. 1.
    Berners-Lee, T.: Weaving the web: the original design and ultimate destiny of the world wide web by its inventor. Harper San Francisco, San Francisco (1999)Google Scholar
  2. 2.
    Brut, M.M., Sedes, F., Dumitrescu, S.D.: A semantic-oriented approach for organizing and developing annotation for e-learning. IEEE Trans. Learn. Technol. 4(3), 239–248 (2011)CrossRefGoogle Scholar
  3. 3.
    Gaeta, M., Orciuoli, F., Paolozzi, S., Salerno, S.: Ontology extraction for knowledge reuse: the e-learning perspective. IEEE Trans. Syst. Man Cybern. Part A: Syst. Humans 41(4), 798–809 (2011)Google Scholar
  4. 4.
    Faure, D., Poibeau, T.: First experiences of using semantic knowledge learned by ASIUM for information extraction task using INTEX. In: Staab, S., Maedche, A., Nédellec, C., Wiemer-Hastings, P. (eds.) Proceeding ECAI Workshop Ontology Learning, vol. 31, CEUR Workshop Proceedings, (2000)Google Scholar
  5. 5.
    Maedche, A., Staab, S.: The text-to-onto ontology learning environment. In: Proceeding 8th international conference conceptual structure, pp. 14–18. Darmstadt, Germany, (2000)Google Scholar
  6. 6.
    Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V.: GATE: a framework and graphical development environment for robust NLP tools and applications. In: Proceeding 40th anniversary meeting association computational linguistics, pp. 1–8 (2002)Google Scholar
  7. 7.
    Navigli, R., Velardi, P., Gangemi, A.: Ontology learning and its application to automated terminology translation. IEEE Intell. Syst. 18(1), 22–31 (2003)CrossRefGoogle Scholar
  8. 8.
    Dean, M., Schreiber, G.: OWL web ontology language reference. W3C recommendation, Feb 2004Google Scholar

Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringJerusalem College of EngineeringChennaiIndia

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