In this study, we proposed a conceptual architecture of web personalization based on subject taxonomy tree and click-through analyses in order to improve the browsing efficiency and user satisfaction. In order to construct user profile, a hierarchal subject taxonomy tree of travel information was built. This tree has five attributes which represent the interests of a single user. Each user has his profile for generating personal categories while searching. The system then adjusts user profiles according to each user’s browsing behavior in order to learn different interests of each user. Textual data in Chinese travel web sites are used for experimental data and a prototype system is implemented in order to evaluate the proposed architecture. The result shows that personal classification is able to improve the outcome of browsing efficiency and user satisfaction on web search.