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Investigating the use of background knowledge for assessing the relevance of statements to an ontology in ontology evolution

Zablith, Fouad; d'Aquin, Mathieu; Sabou, Marta and Motta, Enrico (2009). Investigating the use of background knowledge for assessing the relevance of statements to an ontology in ontology evolution. In: CEUR Workshop Proceedings, 519.

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The tasks of learning and enriching ontologies with new concepts and relations have attracted a lot of attention in the research community, leading to a number of tools facilitating the process of building and updating ontologies. These tools often discover new elements of information to be included in the considered ontology from external data sources such as text documents or databases, transforming these elements into ontology compatible statements or axioms. While some techniques are used to make sure that statements to be added are compatible with the ontology (e.g. through conflict detection), such tools generally pay little attention to the relevance of the statement in question. It is either assumed that any statement extracted from a data source is relevant, or that the user will assess whether a statement adds value to the ontology. In this paper, we investigate the use of background knowledge about the context where statements appear to assess their relevance. We devise a methodology to extract such a context from ontologies available online, to map it to the considered ontology and to visualize this mapping in a way that allows to study the intersection and complementarity of the two sources of knowledge. By applying this methodology on several examples, we identified an initial set of patterns giving strong indications concerning the relevance of a statement, as well as interesting issues to be considered when applying such techniques.

Item Type: Conference or Workshop Item
Copyright Holders: 2009 The Authors
ISSN: 1613-0073
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 23441
Depositing User: Kay Dave
Date Deposited: 21 Oct 2010 12:10
Last Modified: 11 May 2019 07:19
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