A novel personalized Web search model
Abstract
A novel personalized Web search model is proposed. The new system, as a middleware between a user and a Web search engine, is set up on the client machine. It can learn a user’s preference implicitly and then generate the user profile automatically. When the user inputs query keywords, the system can automatically generate a few personalized expansion words by computing the term-term associations according to the current user profile, and then these words together with the query keywords are submitted to a popular search engine such as Yahoo or Google. These expansion words help to express accurately the user’s search intention. The new Web search model can make a common search engine personalized, that is, the search engine can return different search results to different users who input the same keywords. The experimental results show the feasibility and applicability of the presented work.
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