A system based on hierarchical fuzzy clustering for web users profiling

In this paper, we present a system based on an Unsupervised Fuzzy Divisive Hierarchical Clustering (UFDHC) algorithm to determine a hierarchy of profiles of web site typical users from the web access log. These profiles can be extremely useful, for instance, to customize the web site, or to send per...

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Bibliographic Details
Main Authors: Lazzerini, B., Marcelloni, F., Cococcioni, M.
Format: Conference Proceeding
Language:English
Subjects:
Business
Clustering algorithms
Fuzzy systems
Information filtering
Information filters
Navigation
Portals
Telecommunications
Web mining
Web sites
Online Access:Request full text
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Description
Summary:In this paper, we present a system based on an Unsupervised Fuzzy Divisive Hierarchical Clustering (UFDHC) algorithm to determine a hierarchy of profiles of web site typical users from the web access log. These profiles can be extremely useful, for instance, to customize the web site, or to send personalized advertisements. After eliminating categories that have not been accessed by a significant percentage of users and removing the occasional users, the access log data are input to the UFDHC algorithm which clusters the users of the web site into a hierarchy of groups characterized by a set of common interests and represented by a prototype, which defines the profile of the group typical member. To show the effectiveness of our system, we describe how the profiles determined by the UFDHC algorithm from access log data collected along a period of 15 days allow classifying approximately 95% of the users defined by access log data collected during subsequent 60 days.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2003.1244705