Personalized web search using user profile

Current Web search engines are built to serve all users, regardless of special needs of any individual user. So personalization of Web search is to carry out retrieval for each user incorporating his/her interests. A novel query expansion algorithm is proposed in this paper. It is based on a model of personalized web search system, which can learn a user's preference implicitly and then generate the user profile automatically. When the user inputs query keywords, more personalized expansion words are generated by the proposed algorithm, and then these words together with the query keywords are submitted to a popular search engine such as Baidu or Google. These expansion words can help search engines retrieval information for a user according to his/her implicit search intentions, and return different search results to different users who input the same keywords.