Document Type
Conference Proceeding
Publisher
IEEE
Faculty
Faculty of Computing, Health and Science
School
School of Computer and Information Science
RAS ID
1815
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
Access Rights
free_to_read
Comments
This is an Author's Accepted Manuscript of: 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. Available here
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