Paper 187 (Research track)

Improved Categorization of Computer-assisted Ontology Construction Systems: focus on Bootstrapping capabilities

Author(s): Omar Qawasmeh, Antoine Zimmermann, Maxime Lefrançois, Pierre Maret

Abstract: In this research we investigate the problem of ontology construction in both automatic and semi-automatic approaches. Four categories have been defined in the literature to classify such approaches: 1. Conversion or translation, 2. Mining based, 3. External knowledge based, and 4. Frameworks. In this paper we present an updated state of the art of such approaches using this classification. We also propose additional classification of existing work according to features that we
newly introduce: 1. reusability, 2. type of extracted data, 3. bootstrapping capabilities. These features are crucial for ontology construction because they address two key issues: the blank page problem (i.e. starting the development of an ontology from a blank page) and the lack of the availability of the domain experts. We finally describe an approach for ontology construction including the bootstrapping feature. For this feature we take advantage of external knowledge bases. We report on a comparative study between our system and the existing ones on the wine ontology.

Keywords: Ontology; Knowledge base; Ontology Bootstrapping

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