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