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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Castells, P. Fernandez, M. Vallet, D. |
| Copyright Year | 1989 |
| 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 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 |
| Sponsorship | IEEE IEEE Comput. Soc. Tech. Committee on Data Eng IEEE Computer Society |
| File Size | 1087336 |
| File Format | |
| ISSN | 10414347 |
| Volume Number | 19 |
| Issue Number | 2 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-02-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Ontologies Information retrieval Semantic Web Search engines Testing Costs Knowledge management Taxonomy semantic Web. Information retrieval models ontology languages semantic search |
| Content Type | Text |
| Resource Type | Article |
| Subject | Information Systems Computational Theory and Mathematics Computer Science Applications |
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