Document Type

Conference Proceeding

Publisher

IEEE

Faculty

Computing, Health and Science

School

Computer and Information Science

RAS ID

1815

Comments

This conference paper was originally published as: Xiao, J. , & Zhang, Y. (2001). Clustering of Web Users Using Session-based Similarity Measures. Proceedings of 2001 International Conference on Computer Networks and Mobile Computing . (pp. 223-228). Beijing, China. IEEE. Original article available here

Abstract

One important research topic in web usage mining is the clustering of web users based on their common properties. Informative knowledge obtained from web user clusters were used for many applications, such as the prefetching of pages between web clients and proxies. This paper presents an approach for measuring similarity of interests among web users from their past access behaviors. The similarity measures are based on the user sessions extracted from the user's access logs. A multi-level scheme for clustering a large number of web users is proposed, as an extension to the method proposed in our previous work (2001). Experiments were conducted and the results obtained show that our clustering method is capable of clustering web users with similar interests

DOI

10.1109/ICCNMC.2001.962600

 
COinS
 

Link to publisher version (DOI)

10.1109/ICCNMC.2001.962600