Temporal Cluster Migration Matrices for Web Usage Mining

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 of a 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.