Mining the Structure of User Activity using Cluster Stability

Abstract

Recent research has explored web user session clustering as a means of understanding user activity and interests on theWorld Wide Web. Though the proposed techniques have proven to be useful and effective, they require that one either specify the number of clusters in advance or browse a large hierarchy of clusters to find the optimal depth at which to describe user activity. In this paper, we examine the utility of a stability-based technique for automatically determining the optimal number of clusters in the context of web user session clustering.We present two case studies evaluating the techniques effectiveness.