Relational clustering based on a new robust estimator with application to Web mining
Olfa Nasraoui, Raghu J. Krishnapuram, Anupam Joshi · 2003
Mining typical user profiles and URL associations from the vast amount of access logs is an important component of Web personalization. In this paper, we define the notion of a ""user session" as being a temporally compact sequence of Web accesses by a user. We also define a dissimilarity measure between two Web sessions that captures the organization of a Web site. To cluster the user sessions based on the pairwise dissimilarities, we introduce the relational fuzzy c-maximal density estimator (RFC-MDE) algorithm. RFC-MDE is robust and can deal with outliers that are typical in this application. We show real examples of the use of RFC-MDE for extraction of user profiles from log data, and and compare its performance to the standard non-Euclidean fuzzy c-means.