Web User Clustering Analysis based on KMeans Algorithm

摘要：

As one of the most important tasks of Web Usage Mining (WUM), web user clustering, which establishes groups of users exhibiting similar browsing patterns, provides useful knowledge to personalized web services. In this paper, we cluster web users with KMeans algorithm based on web user log data. Given a set of web users and their associated historical web usage data, we study their behavior characteristic and cluster them. Experiment results show the feasibility and efficiency of such algorithm application. Web user clusters generated in this way can provide novel and useful knowledge for various personalized web applications.

关键词： web user clustering Kmeans vector matrix similarity

作者: JinHuaXu HongLiu

作者单位: Computer and Information Engineering College Zhejiang Gongshang University HangZhou, China

会议类型: 国际会议

会议名称: 2010 International Conference on Information,Networking and Automation(2010 IEEE信息网络与自动化国际会议 ICINA 2010)

会议地点: 昆明

会议语种:英文

页码: 6-9

在线出版日期: 2010-10-17（万方平台首次上网日期，不代表论文的发表时间）