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A Hybrid Approach to Personalize Web Search with User Diversity Prediction
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It is still an area of research whether personalization is consistently effective on different queries for different users and under different search contexts. Among the different techniques used to improve the web search a click based approach found to be more permissive if the user browse history is available. Here preliminarily a click based approach is implemented in the client side system by storing the client search information in the local system. Then from this information, user’s topical interest pattern is mined and a hybrid approach of both these techniques is implemented. It is also found that most of the personalization techniques apply personalization uniformly irrespective of any consideration. A Click Entropy is used here as a technique to predict the need of personalization. Using a prediction model is also found to be a solution and it is better than using the personalization simply for all queries.
Keywords
Click Entropy, ODP, P-Click, Topical Interest.
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