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Deep Web Query Extraction Algorithm for Information Retrieval System

There are number of data sources available on the web i.e. there are collections of data that are distributed across multiple physical locations but these deep web contents are only accessible through query interfaces. In response to user query, too many results are return in response, so this paper presents a framework to solve the problem of data extraction and ranking. Ranking calculates by probabilities of attribute for query in particular user and in overall data and then find mean of both probabilities. Then ranking is done according to mean probability. KeywordRanking, Mean Probability