Mining User Preferred Knowledge from Web-Log

How to mine user-interested path from Web-log is an important and challengeable research topic. On the analysis of the present algorithm´s advantages and disadvantages, we propose a new algorithm for discovering such expected Web pages. Through computing the probability of the document which is recommended to the user, we can mine user preferred sub-paths. Accordingly, all the sub-paths are merged, and user preferred paths are formed. Experiments showed that it was more precise than previous algorithm. It´s suitable for Web site based application, such as to optimize Web site´s topological structure or to design personalized services