Research on Clustering Algorithm Based on Web Log Mining

Abstract

People’s online business behaviour has become more and more frequent. Internet service providers are beginning to find ways to obtain the interests and hobbies of users in order to provide targeted services to users. Analysis of user behavior based on Web logs can obtain valuable information from users. User clustering based on Web logs can cluster users according to user behavior, and then analyze user access patterns, providing a good solution for problem solving. This article introduces the concept and process of data mining, the classification and process of Web data mining, and then analyzes the K-Means clustering algorithm. The class-centered algorithm avoids clustering and only obtains the local optimal solution, and it can reduce the algorithm iteration time and improve the clustering quality.