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Identifying key concepts in an ontology, through the integration of cognitive principles with statistical and topological measures

Peroni, Silvio; Motta, Enrico and d'Aquin, Mathieu (2008). Identifying key concepts in an ontology, through the integration of cognitive principles with statistical and topological measures. In: 3rd Asian Semantic Web Conference (ASWC 2008), 08-11 Dec 2008, Bangkok, Thailand, pp. 242–256.

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DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1007/978-3-540-89704-0_17
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Abstract

In this paper we address the issue of identifying the concepts in an ontology, which best summarize what the ontology is about. Our approach combines a number of criteria, drawn from cognitive science, network topology, and lexical statistics. In the paper we show two versions of our algorithm, which have been evaluated against the results produced by human experts. We report that the latest version of the algorithm performs very well, exhibiting an excellent degree of correlation with the choices of the experts. While the generation of automatic methods for ontology summarization is an interesting research issue in itself, the work described here also provides a basis for novel approaches to a variety of ontology engineering tasks, including ontology matching, automatic classification, ontology modularization, and ontology evaluation.

Item Type: Conference Item
Copyright Holders: 2008 Springer-verlag Berlin Heidelberg
ISSN: 0302-9743
Keywords: ontology; semantic web; key concepts; ontology summarization; natural categories; cognitive science
Academic Unit/Department: Knowledge Media Institute
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 23484
Depositing User: Kay Dave
Date Deposited: 20 Oct 2010 11:57
Last Modified: 20 Nov 2013 17:52
URI: http://oro.open.ac.uk/id/eprint/23484
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