A Generalization-Based Approach to Clustering of Web Usage Sessions
Abstract
The clustering of Web usage sessions based on the access patterns is studied. Access patterns of Web users are extracted from Web server log files, and then organized into sessions which represent episodes of interaction between the Web users and the Web server. Using attribute-oriented induction, the sessions are then generalized according to a page hierarchy which organizes pages based on their contents. These generalized sessions are finally clustered using a hierarchical clustering method. Our experiments on a large real data set show that the approach is efficient and practical for Web mining applications.
Recommended Citation
Y. Fu et al., "A Generalization-Based Approach to Clustering of Web Usage Sessions," Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1836, pp. 21 - 38, Springer, Jan 2000.
The definitive version is available at https://doi.org/10.1007/3-540-44934-5_2
Department(s)
Computer Science
International Standard Book Number (ISBN)
978-354067818-2
International Standard Serial Number (ISSN)
1611-3349; 0302-9743
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Springer, All rights reserved.
Publication Date
01 Jan 2000
