Visualization of web usage patterns

Abstract

We present a novel approach to visualize web usage patterns by closely coupling the visual rendering process to the data mining technique. In the first step we use Relational Fuzzy Subtractive Clustering as the mining technique to perform fuzzy clustering on web usage sessions. In the second step, we use conventional metric Multidimensional Scaling to obtain an initial positional configuration in 3D space for the cluster centers, and then apply a modified Sammon Mapping technique to further optimize the 3D positions. In the last step, we use the dominant membership values to assign positions to all the other sessions in the given dataset. This is computationally very efficient and at the same time retains the fidelity of the interrelationships much better. We have developed a running prototype of the proposed approach and have demonstrated the utility through experiments using several datasets, including a fairly large web usage dataset of about 100,000 log records. © 2006 IEEE.