User-Centred Ontology Learning for Knowledge Management

  • Christopher Brewster
  • Fabio Ciravegna
  • Yorick Wilks
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2553)


Automatic ontology building is a vital issue in many fields where they are currently built manually. This paper presents a user-centred methodology for ontology construction based on the use of Machine Learning and Natural Language Processing. In our approach, the user selects a corpus of texts and sketches a preliminary ontology (or selects an existing one) for a domain with a preliminary vocabulary associated to the elements in the ontology (lexicalisations). Examples of sentences involving such lexicalisation (e.g. ISA relation) in the corpus are automatically retrieved by the system. Retrieved examples are validated by the user and used by an adaptive Information Extraction system to generate patterns that discover other lexicalisations of the same objects in the ontology, possibly identifying new concepts or relations. New instances are added to the existing ontology or used to tune it. This process is repeated until a satisfactory ontology is obtained. The methodology largely automates the ontology construction process and the output is an ontology with an associated trained leaner to be used for further ontology modifications.


Knowledge Management Concept Hierarchy User Validation Ontology Construction Knowledge Capture 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Christopher Brewster
    • 1
  • Fabio Ciravegna
    • 1
  • Yorick Wilks
    • 1
  1. 1.Department of Computer ScienceUniversity of SheffieldSheffieldUK

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