Re-Ranking Web Search Result for Semantic Searching

!!!! Bi-Annual Double Blind Peer Reviewed Refereed Journal !!!!

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Rutuja Ajmire - M.Tech 2nd year CSE Dept, Government College of Engineering, Amravati (Maharashtra),India

Prof.A.V.Deorankar - Assistant professor CSE Dept, Government College of Engineering, Amravati (Maharashtra), India

Dr. P. N. Chatur - Head of Department CSE Dept, Government College of Engineering, Amravati (Maharashtra), India


Information retrieval mechanisms from the web become tedious as the amount of information is growing dynamically day by day. In this paper, it is observed that the users rarely have the patience to navigate for content beyond the first five web result pages. This paper shows the common problems of existing search engine and proposed a new approach based on the ontological search engine. The aim of this paper is to improve the web search result using semantic similarity which will improve the quality of search engines First obtain top N results returned by search engine such as Google, and then use semantic similarities between the Content obtain from the web search result and the users query. A semantic similarity algorithm based on WordNet ontology which is used to calculate the similarity of each snippet to each of the return result. And then based on the similarity re-ranking is performed. A balanced similarity ranking method combined with Google’s rank. Here first we convert the ranking position to an importance score for semantics instead of keyword matching which can better adapt timeliness of the pages is used to rank these Web pages.

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