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In this paper, we propose ART1 neural network clustering algorithm to groupusers according to their Web access patterns. We compare the quality ofclustering of our ART1 based clustering technique with that of the K-Means andSOM clustering algorithms in terms of inter-cluster and intra-clusterdistances. The results show the average inter-cluster distance of ART1 is highcompared to K-Means and SOM when there are fewer clusters. As the number ofclusters increases, average inter-cluster distance of ART1 is low compared toK-Means and SOM which indicates the high quality of clusters formed by ourapproach.

Dynamic Grouping of Web Users Based on Their Web Access Patterns using ART1 Neural Network Clustering Algorithm