Adaptive Web Sites: Conceptual Cluster Mining
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Model-Based Clustering and Visualization of Navigation Patterns on a Web Site
Data Mining and Knowledge Discovery
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
Analysis of cluster migrations using self-organizing maps
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
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Time can play a crucial role in the analysis of web usage. Temporal data mining has been an active area of research. However, there is little work on the analysis of cluster memberships over time. Typical clustering operations in web mining involve finding natural groupings of web resources or web users. Changes in clusters can provide important clues about the changing nature of the usage of a web site, as well as changing loyalties of web users. This paper addresses two different types of temporal changes in cluster analysis. The changes in cluster compositions over time and changes in cluster memberships of individual web users. The paper also proposes the concept of temporal cluster migration matrices (TCMM). The proposed matrices are shown to be useful for analyzing the changing nature ofa web site as well as changing patronages of individual web users. TCMM can be used as a visualization technique to study results obtained from temporal data mining, which can be more complex because of the additional time dimension.