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An Ontology Based Meta-Search Engine for Effective Web Page Retrieval
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Abstract
Searching on the web using Search engines such as Google, Bing, Ask have become an extremely common way of locating information. Searches are factorized by using either term or keyword sequentially or through short sentences. In order to make the searching more specific on certain information met-search engines are used, since the searches using meta- search engine are customizable. Meta search engines provide a uniform query interface for Internet users to search for information from the Web. In this paper, a method for search engine is described which deals with the composition of search results from different search engines under specific criteria. The main feature of the proposed approach is concept extraction from the web documents with the help of WordNet ontology. The proposed approach identifies three attributes and defines three matrices one each for the three attributes of the method. The matrix is a concept matrix, which contains the set of concept extracted from the web documents. The second matrix is a title matrix for the title tags of the web and finally a vector matrix is defined for the multiple words that combined to form a concept. The evaluation of the proposed approach is based on the evaluation factor TREC Style Average Prevision at cutoff N (TSAP/N). The highest value of TSAP is shown by the concept computer science, having listed a TSAP value of 0.90 at N value 10.
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