Ontology Learning Part One — on Discovering Taxonomic Relations from the Web

  • Alexander Maedche
  • Viktor Pekar
  • Steffen Staab


Ontologies may help to facilitate the finding and use of Web information. However, the engineering of an ontology may turn out to be expensive and time-consuming. Therefore, we exploit ontology learning techniques that automate ontology engineering to some extent. In this chapter, we focus on the learning of the taxonomic backbone of ontologies, presenting a survey on algorithms as well as on some new ideas that consider the structure of existing ontology parts. Eventually, we describe an evaluation of our proposal and give concrete results.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 14.
    H. Assadi: Construction of a regional ontology from text and its use within a documentary system. In N. Guarino (ed.), Formal Ontology in Information Systems, Proc. FOIS-98, Trento, Italy, 1999 (1999) pp. 236–249Google Scholar
  2. 14.2
    I. Dagan, L. Lee, F. Pereira: Similarity-based models of word coocurrence probabilities. Machine Learning, 34 (1) 43–69 (1999)MATHCrossRefGoogle Scholar
  3. 14.3
    D. Faure, C. Nedellec: A corpus-based conceptual clustering method for verb frames and ontology acquisition. In: In LREC Workshop on Adapting Lexical and Corpus Resources to Sublanguages and Applications, Granada, Spain, May 1998 (1998)Google Scholar
  4. 14.4
    G. Greffenstette, M.A. Hearst: A method for refining automatically-discovered lexical relations: combining weak techniques for stronger results. In: Proc. the Workshop on Statistically-Based Natural Language Programming Techniques, AAAI Press, Menlo Park, CA, 1992 (1992)Google Scholar
  5. 14.5
    U. Hahn, Schnattinger: Ontology engineering via text understanding. In: IFIP’98 - Proc. the 15th World Computer Congress (Vienna and Budapest, 1998 )Google Scholar
  6. 14.6
    P.M. Hastings: Automatic Acquisition of Word Meaning from Context. PhD thesis, University of Michigan (1994)Google Scholar
  7. 14.7
    M.A. Hearst: Automatic acquisition of hyponyms from large text corpora. In: Proc. The 14th International Conference on Computational Linguistics. Nantes, France (1992)Google Scholar
  8. 14.8
    M.A. Hearst, H. Schütze: Customizing a lexicon to better suit a computational task. In: Proc. of the ACL-SIGLEX Workshop on Acquisition of Lexical Knowledge from Text, Columbus, OH, USA (1993)Google Scholar
  9. 14.9
    J. Hobbs: The generic information extraction system. In: Proceedings of the Fifth Message Understanding Conference (MUC-5), Morgan Kaufmann, 1993 (1993)Google Scholar
  10. 14.10
    T. Hofmann: The Cluster-Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data. In: Proc. the 16th International Conference on Artificial Intelligence (IfCAI-99), Stockholm, Sweden, 1999 (1999) pp. 682–587Google Scholar
  11. 14.11
    L. Kaufman. P.J. Rousseeuw: Finding Groups in Data: An Introduction to Cluster Analysis (John Wiley, 1990 )Google Scholar
  12. 14.12
    J.-U. Kietz, R. Volz, A. Maedche: Semi-automatic ontology acquisition from a corporate intranet. In: Proc. International Conference on Grammar Inference (ICGI-2000), LNAI (Springer, Berlin, 2000 )Google Scholar
  13. 14.13
    L. Lee: Measures of distributional similarity. In: Proc. the ACL’99 (1999) pp. 25–32Google Scholar
  14. 14.14
    L. Lee: Measures of distributional similarity. In: Proc. of the 37th Annual Meeting of the Association for Computational Linguistics (1999) pp. 25–32Google Scholar
  15. 14.15
    A. Maedche, S. Staab: Discovering conceptual relations from text. In: ECAI-2000 - Proc. the 13th European Conference on Artificial Intelligence ( IOS Press, Amsterdam, 2000 )Google Scholar
  16. 14.16
    A. Maedche, S. Staab: Mining ontologies from text. In: Proc. EKAW-2000, Juan-LesPins, France, 2000, LNAI-1937 (Springer, 2000 )Google Scholar
  17. 14.17
    A. Maedche, S. Staab: Ontology learning for the semantic web. IEEE Intelligent Systems, 16 (2) (2001)Google Scholar
  18. 14.18
    C.D. Manning, H. Schuetze: Foundations of Statistical Natural Language Processing ( MIT Press, Cambridge, MA, 1999 )MATHGoogle Scholar
  19. 14.19
    E. Morin: Automatic acquisition of semantic relations between terms from technical corpora. In: Proc. the Fifth International Congress on Terminology and Knowledge Engineering (TKE’99) (1999)Google Scholar
  20. 14.
    E Pereira, N. Tishby, L. Lee: Distributation Clustering of English Words. In: Proc. the ACL-93, 1993 (1993) pp. 183–199Google Scholar
  21. 14.21
    P.S. Resnik: Selection and Information: A Class-based Approach to Lexical Relationships ( PhD thesis, University of Pennsylania, 1993 )Google Scholar
  22. 14.22
    M. Sanderson, B. Croft: Deriving Concept Hierarchies from Text. In: Proc. The International Conference on Information Retrieval — SIGIR’99, August 1999, Berkley CA, USA (1999)Google Scholar
  23. 14.23
    S. Staab, C. Braun, A. Düsterhöft, A. Heuer, M. Klettke, S. Melzig, G. Neumann, B. Prager, J. Pretzel, H.-P. Schnurr, R. Studer, H. Uszkoreit, B. Wrenger: GETESS - searching the Web exploiting German texts. In: Proc. the 3rd Workshop on Cooperative Information Agents, LNCS 1652 ( Springer, Berlin, 1999 )Google Scholar
  24. 14.24
    S. Staab, H.-P. Schnurr, R. Studer, Y. Sure: Knowledge processes and ontologies IEEE Intelligent Systems, 16 (1) (2001)Google Scholar
  25. 14.25
    York Sure, Michael Erdmann, Juergen Angele, Steffen Staab, Rudi Studer, Dirk Wenke: Ontoedit: Collaborative ontology development for the semantic Web. In: Proc. 1st International Semantic Web Conference (ISWC2002), June 9–12th, 2002, Sardinia, Italy, LNCS (Springer, 2002 )Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Alexander Maedche
    • 1
  • Viktor Pekar
    • 2
  • Steffen Staab
    • 3
    • 4
    • 5
  1. 1.FZIUniversity of KarlsruheGermany
  2. 2.Bashkir State UniversityUfaRussia
  3. 3.Institute AIFBUniversity of KarlsruheGermany
  4. 4.Learning LabLower Saxony HannoverGermany
  5. 5.Ontoprise GmbHKarlsruheGermany

Personalised recommendations