Abstract
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 KBs to improve search over large document repositories. Our approach includes an ontology-based scheme for the semi-automatic 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 keyword-based search to achieve tolerance to KB incompleteness. Our proposal is illustrated with sample experiments showing improvements with respect to keyword-based search, and providing ground for further research and discussion.
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Vallet, D., Fernández, M., Castells, P. (2005). An Ontology-Based Information Retrieval Model. In: Gómez-Pérez, A., Euzenat, J. (eds) The Semantic Web: Research and Applications. ESWC 2005. Lecture Notes in Computer Science, vol 3532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11431053_31
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DOI: https://doi.org/10.1007/11431053_31
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