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 automati- cally. When the user inputs query keywords, the system can auto- matically generate a few personalized expansion words by com- puting 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 key- words. The experimental results show the feasibility and applica- bility of the presented work. 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 preferences implicitly and then generate the user profile automati- cally. When the user inputs query keywords, the system can auto-matically generate a few personalized expansion words by com- puting 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 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 key-words. The experimental results show the feasibility and applica- bility of the presented work.