The Quest of Information Retrieval in Semantic Web Miriam Fernández
This event took place on 13th September 2006 at 11:30am (10:30 GMT)
Knowledge Media Institute, Berrill Building, The Open University, Milton Keynes, United Kingdom, MK7 6AA
Semantic search has been one of the motivations of the Semantic Web since it was envisioned. In my thesis I research the development of a new retrieval model for the exploitation of ontology-based knowledge bases to improve search over large document repositories. In this 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, my current 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. The method has been tested on corpora of significant size, showing promising results respect to keyword-based search, and providing ground for further analysis and research.
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