Name
Abstract | ||
|---|---|---|
In this paper, we present AntClust, an ant based clustering algo- rithm and its application to the Web usage mining problem. We define a Web session as a weighted multi-modal vector and we also develop a similarity measure between two sessions. We show that the partitions found by AntClust are stable on a data set made of real sessions extracted from a Web site of the University of Tours. Contrary to some other studies, we do not only consider the trans- actions model to describe the sessions. We show that our algorithm performs well and is able to find non-noisy clusters when dealing with sessions defined by a vector containing the number of hits recorded for each of the Web page. |
Year | Venue | Keywords |
|---|---|---|
2003 | WWW Posters | artifial ants,web usage mining,clustering,web pages,ant colony |
Field | DocType | Citations |
Data mining,Similarity measure,Computer science,Cluster analysis,Web site,Artificial Ants | Conference | 3 |
PageRank | References | Authors |
0.50 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolas Labroche | 1 | 139 | 17.87 |
| Nicolas Monmarché | 2 | 305 | 32.73 |
| Gilles Venturini | 3 | 660 | 82.45 |