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An adaptation of the Vector-Space Model for ontology-based information retrieval

Castells, Pablo; Fernandez, Miriam and Vallet, David (2007). An adaptation of the Vector-Space Model for ontology-based information retrieval. IEEE Transactions on Knowledge and Data Engineering, 19(2) pp. 261–272.

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Semantic search has been one of the motivations of the Semantic Web since it was envisioned. We propose a model for the exploitation of ontology-based knowledge bases to improve search over large document repositories. In our view of Information Retrieval on the Semantic Web, a search engine returns documents rather than, or in addition to, exact values in response to user queries. For this purpose, our approach includes an ontology-based scheme for the semiautomatic annotation of documents and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with conventional keyword-based retrieval to achieve tolerance to knowledge base incompleteness. Experiments are shown where our approach is tested on corpora of significant scale, showing clear improvements with respect to keyword-based search.

Item Type: Journal Item
Copyright Holders: 2007 IEEE
ISSN: 1041-4347
Project Funding Details:
Funded Project NameProject IDFunding Body
Not SetNot SetEuropean Commission [FP6-027685—MESH]
Not SetNot SetSpanish Ministry of Science and Education [TIN2005-06885]
Keywords: information retrieval models; ontology languages; semantic web; semantic search
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: 28589
Depositing User: Kay Dave
Date Deposited: 26 Apr 2011 09:49
Last Modified: 07 Dec 2018 09:53
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