When a query is submitted to search engine, user have in mind a fixed goal. Search engine gives thousands of results for such a query. Most of them are not useful for user so time and energy is wasted. For increasing retrieval precision, some new method provides manually verified answers to Frequently Asked Queries (FAQs). In this paper we are clustering the feedback session by using Fuzzy c-means algorithm. Also we use method to map feedback sessions to pseudo-documents which can efficiently reflect required data. Then, we evaluate the "Classified Average Precision (CAP)" of restructured web search results. In the area of web mining, more importance is given to fast and accurate extraction of information. Query suggestions provided by the search engine will help to find the user needs. But it may cover broad topics, so this may not be solution for achieving a better search result. Also same queries have different goals for different users. The analysis of user search goal improves the relevance and user satisfaction of the search engine. This method analyzes the user query and restructure the search results.

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Navi Mumbai

Papers

User search feedback behavior using fuzzy c mean