By Topic

Clustering Web sessions by sequence alignment

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Weinan Wang ; Alberta Univ., Edmonton, Alta., Canada ; O. R. Zaiane

In the context of Web mining, clustering could be used to cluster similar click-streams to determine learning behaviours in the case of e-learning, or general site access behaviours in e-commerce. Most of the algorithms presented in the literature to deal with clustering Web sessions treat sessions as sets of visited pages within a time period and don't consider the sequence of the click-stream visitation. This has a significant consequence when comparing similarities between Web sessions. We propose in this paper a new algorithm based on sequence alignment to measure similarities between Web sessions where sessions are chronologically ordered sequences of page accesses.

Published in:

Database and Expert Systems Applications, 2002. Proceedings. 13th International Workshop on

Date of Conference:

2-6 Sept. 2002