Modeling and Intelligent Analysis of Web User Behavior of WEB User Behavior

摘要

The core research of Web mining is interest association rule in Web logs and clustering algorithm of user browsing behavior. Traditional association mode and browsing path have certain advantage in browsing path for the user, while they cannot provide accurate recommendation in the important area at the same page. Therefore, based on the association rules of users' interest, an intelligent user interest association rule is proposed in this paper, integrated with Web area partition. It comes from the choice of area of current network users and different interest degree of user browsing on the web. Then, related mining algorithm is put forward based on interest area. The algorithm improves the accuracy of recommendation of single page area by interest degree of page browsing and weight computation of click-stream data. Finally the effectiveness of the intelligent system is verified by the experiments.