Data Mining Framework for Web Search Personalization

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Mrs Geetha S
Prof.Rachana Dhannawat

Abstract

Web users may have diverse search objectives when they search by giving queries and submitting it to a search engine. The inference and analysis of user search goals can be very useful for providing an expected result for a user search query. The below mentioned framework will give the data identified with the client objectives by analysing search engine query logs. User would practically benefit if search results could be displayed in different categories with manual rating so that user defined highest rated URLs are displayed at the top. It will help user to save effort and time in retrieving the required information. For achieving this feedback sessions are constructed from user click-through logs and pseudo-documents are generated. Pseudo-documents represent the feedback sessions for clustering. Using “Classified Average Precision (CAP)†criterion the performance of inferring user search goals can be evaluated.

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