Abstract
In this paper, we attempt to propose a two-phased ontology selection approach. Users can describe their requirements through a two-level requirement analysis model. The coarse-level analysis model is quite simple, only used for describing the main domains covered by the desired ontology and for selecting a fixed number of promising candidate source ontologies. The fine-level analysis model then refines the coarse-level model by defining the details in each domain. It is used to find the best matched ontology from the candidates from phase 1. The token extraction module and the WordNet system are also used to help for flexible match. The proposed selection approach can help easily find an appropriate ontology for a new application.
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Hong, TP., Chang, WC., Lin, JH. (2005). A Two-Phased Ontology Selection Approach for Semantic Web. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3684. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11554028_56
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DOI: https://doi.org/10.1007/11554028_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28897-8
Online ISBN: 978-3-540-31997-9
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