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If the topic is very vast and the query is ambiguous, the users may be having different search goals when they submit the queries to a search engine. The goals of the users can be analysed in order to make the search engine results more relevant. In this paper, the Click through Logs are analyzed to create feedback Sessions. These feedback Sessions generated are used to create Pseudo documents . These Pseudo documents are further analysed and clustered based on Kmeans clustering algorithm. Then these clustered documents are checked for relevance evaluvation using Classified Average Precision(CAP).

User Search Goal Prediction based on Feedback Sessions