Click based inferring of user search goals using pseudo document

The user enters any query to find desired information. To discover number of user search goals and representing each goal with some keyword, we first infer user search goals for a query by clustering feedback sessions. For that, we use a concept of pseudo document, which is the revised version of feedback session. Then the user search goals are determined by clustering the pseudo documents and it also represents the cluster with some keyword. Evaluation is done by using the Classified Average Precision (CAP), it is used to evaluate the performance of the restructured web search results. The existing system is using the k means clustering algorithm but in proposed system, we are using bisecting k means clustering algorithm which is increasing the efficiency of result. After the segmented result formation, the result in the every segment is reorganized as per number of clicks of URLs. The link which is clicked more number of times will appear at first location in the segment. This reduces the time requirement for searching.