Methods and Tools for Automatic Construction of Ontologies from Textual Resources: A Framework for Comparison and Its Application

  • Toader GherasimEmail author
  • Mounira Harzallah
  • Giuseppe Berio
  • Pascale Kuntz
Part of the Studies in Computational Intelligence book series (SCI, volume 471)


Over the recent years, several approaches and tools for the automatic construction of ontologies from textual resources have been proposed. This paper provides a comparative analysis of four well known approaches and related tools among existing ones. The selected approaches and related tools indeed cover all the steps of the ontology construction process. In the first part of the paper, we introduce Methontology and related task i.e. a well-known reference methodology designed for the manual construction of ontology; then, according to Methontology, we analyze and classify detailed subtasks required by those approaches. Based on this uniform classification, we provide a very detailed comparison of those approaches: we explain the main techniques and introduce tools used in the various subtasks of each approach and we highlight the main similarities and differences between the techniques used in comparable subtasks belonging to distinct approaches. In the second part of the paper, we introduce various measures for evaluating tools effectiveness wrt a manually constructed ontology. Then, we evaluate and compare the key tools supporting those approaches by using the provided measures and a specific set of textual resources.


External Resource Pattern Learning Taxonomic Relation Automatic Construction Compound Term 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. [Aime et al., 2009]
    Aime, X., Furst, F., Kuntz, P., Trichet, F.: Gradients de prototypicalité appliqués à la personnalisation d’ontologies. In: Actes de la Conférence Ingénierie des Connaissances (IC 2009), pp. 241–252 (2009)Google Scholar
  2. [Bourigault and Lame, 2002]
    Bourigault, D., Lame, G.: Analyse distributionnelle et structuration de terminologie. application á la construction d’une ontologie documentaire du droit. Traitement Automatique des Langues 43(1), 129–150 (2002)Google Scholar
  3. [Buitelaar et al., 2005]
    Buitelaar, P., Cimiano, P., Magnini, B.: Ontology learning from text: an overview. In: Ontology Learning from Text: Methods, Applications and Evaluation, pp. 3–12. IOS Press (2005)Google Scholar
  4. [Cimiano and Volker, 2005]
    Cimiano, P., Völker, J.: Text2Onto - a Framework for Ontology Learning and Data-driven Change Discovery. In: Montoyo, A., Muńoz, R., Métais, E. (eds.) NLDB 2005. LNCS, vol. 3513, pp. 227–238. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  5. [Corcho et al., 2005]
    Corcho, Ó., Fernández-López, M., Gómez-Pérez, A., López-Cima, A.: Building Legal Ontologies with METHONTOLOGY and WebODE. In: Benjamins, V.R., Casanovas, P., Breuker, J., Gangemi, A. (eds.) Law and the Semantic Web. LNCS (LNAI), vol. 3369, pp. 142–157. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  6. [Fernandez et al., 1997]
    Fernández-López, M., Gómez-Pérez, A., Juristo, N.: Methontology: From ontological art towards ontological engineering. In: Proc. of the AAA 1997 Spring Symposium Series on Ontological Engineering, pp. 33–40 (1997)Google Scholar
  7. [Gherasim et al., 2011]
    Gherasim, T., Harzallah, M., Berio, G., Kuntz, P.: Analyse comparative de méthodologies et d’outils de construction automatique d’ontologies á partir de ressources textuelles. In: EGC 2011 (2011)Google Scholar
  8. [Gruber, 1993]
    Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquisition 5(2), 199–220 (1993)CrossRefGoogle Scholar
  9. [Harris, 1968]
    Harris, Z.: Mathematical Structures of Language. John Wiley and Son (1968)Google Scholar
  10. [Hearst, 1992]
    Hearst, M.A.: Automatic acquisition of hyponyms from large text corpora. In: Proceedings of the 14th International Conference on Computational Linguistics, pp. 539–545 (1992)Google Scholar
  11. [Maynard et al., 2009a]
    Maynard, D., Funk, A., Peters, W.: Nlp-based support for ontology lifecycle development. In: Proc. of ISWC Workshop on Collaborative Construction, Management and Linking of Ontologies (2009a)Google Scholar
  12. [Maynard et al., 2009b]
    Maynard, D., Funk, A., Peters, W.: Sprat: a tool for automatic semantic pattern-based ontology population. In: Proc. of the Int. Conf. for Digital Libraries and the Semantic Web (2009b)Google Scholar
  13. [Navigli and Velardi, 2004]
    Navigli, R., Velardi, P.: Learning domain ontologies from document warehouses and dedicated web sites. Computational Linguistics 30(2), 151–179 (2004)zbMATHCrossRefGoogle Scholar
  14. [Navigli and Velardi, 2005]
    Navigli, R., Velardi, P.: Structural semantic interconnections: A knowledge-based approach to word sense disambiguation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 27(7), 1075–1086 (2005)CrossRefGoogle Scholar
  15. [Navigli et al., 2003]
    Navigli, R., Velardi, P., Gangemi, A.: Ontology learning and its application to automated terminology translation. IEEE Intelligent Systems 18(1), 22–31 (2003)CrossRefGoogle Scholar
  16. [Nazarenko and Hamon, 2002]
    Nazarenko, A., Hamon, T.: Structuration de terminologie: quels outils pour quelles pratiques? Traitement Automatique des Langues. Structuration de Terminologie 43(1), 7–18 (2002)Google Scholar
  17. [Nedellec, 2006]
    Nedellec, C.: Semantic class learning and syntactic resources tuning. Technical report, Deliv. 6.4a for ALVIS (Superpeer semantic Search Engine) Project (2006)Google Scholar
  18. [Osborne et al., 2009]
    Osborne, J., Flatow, J., Holko, M., Lin, S., Kibbe, W., Zhu, L., Danila, M., Feng, G., Chisholm, R.L.: Annotating the human genome with disease ontology. BMC Genomics 10(supl.1), 63–68 (2009)Google Scholar
  19. [Park et al., 2011]
    Park, J., Cho, W., Rho, S.: Evaluating ontology extraction tools using a comprehensive evaluation framework. Data Knowl. Eng. 69, 1043–1061 (2011)CrossRefGoogle Scholar
  20. [Salton et al., 1975]
    Salton, G., Yang, C., Yu, C.: A theory of term importance in automatic text analysis. Journal of the American Society for Information Science 26, 33–34 (1975)CrossRefGoogle Scholar
  21. [Velardi et al., 2007]
    Velardi, P., Cucchiarelli, A., Pétit, M.: A taxonomy learning method and its application to characterize a scientific web community. IEEE Trans. on Knowl. and Data Eng. 19(2), 180–191 (2007)CrossRefGoogle Scholar
  22. [Velardi et al., 2008]
    Velardi, P., Navigli, R., D’Amadio, P.: Mining the web to create specialized glossaries. IEEE Intelligent Systems 23(5), 18–25 (2008)CrossRefGoogle Scholar
  23. [Volker and Sure, 2006]
    Volker, J., Sure, Y.: Data-driven change discovery - evaluation. Technical report, Deliv. D3.3.2 for SEKT Project, Instit. AIFB, Univ. of Karlsruhe, SEKT Deliv. (2006)Google Scholar
  24. [Zouaq and Nkambou, 2010]
    Zouaq, A., Nkambou, R.: A Survey of Domain Ontology Engineering: Methods and Tools. In: Nkambou, R., Bourdeau, J., Mizoguchi, R. (eds.) Advances in Intelligent Tutoring Systems. SCI, vol. 308, pp. 103–119. Springer, Heidelberg (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Toader Gherasim
    • 1
    Email author
  • Mounira Harzallah
    • 1
  • Giuseppe Berio
    • 2
  • Pascale Kuntz
    • 1
  1. 1.LINA, UMR 6241 CNRSNantesFrance
  2. 2.LABSTICC, UMR 6285 CNRSBrestFrance

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