User-centred ontology learning for knowledge management

Brewster, Christopher; Ciravegna, Fabio and Wilks, Yorick (2002). User-centred ontology learning for knowledge management. IN: 6th International Conference on Applications of Natural Language to Information Systems, NLDB 2002 Stockholm, Sweden, June 27–28, 2002 Revised Papers. Andersson, Birger; Bergholtz, Maria and Johannesson, Paul (eds) Lecture Notes in Computer Sciences . Berlin (DE): Springer.


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.

Publication DOI:
Divisions: Aston Business School > Operations & information management
Event Title: 7th International Conference on Applications of Natural Language to Information Systems
Event Type: Other
Event Dates: 2002-06-27 - 2002-06-28
Uncontrolled Keywords: automatic ontology building,user-centred methodology,r ontology construction,Machine Learning and Natural Language Processing,preliminary vocabulary,lexicalisations,adaptive Information Extraction system
Published Date: 2002-06


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