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Quest-semantic a query based personalization for enhancing search engine on web

Author:

Rekha, M. and Meyyappan, T.

Subject Area:

Physical Sciences and Engineering

Abstract:

In this paper, the authors propose a framework for building semantic web support for intelligent search using RDF, ontology and SPARQL queries. Existing Key Word Searching yields 60% accurate results remaining 40% are unwanted results. On the other hand, getting results using RDBMS query processing is very slow. Current keyword-based search engines can’t fully capture the intrinsic richness of natural language; synonymy and polysemy. We propose a Semantic Web search technique which yields 90% accurate results. Semantic web Search employs Annotation Engine and RDF. In the proposed technique, Flat files and Sparql queries are used, which is very fast. Results produced by the proposed technique are provided.

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