Mining web access logs using relational competitive fuzzy clustering
In Proceedings of the Eight International Fuzzy Systems Association World Congress, (1999)Abstract
The proliferation of information on the World-Wide Web has made the personalization of this information space a necessity. An important part of Web personalization is to mine typical user profiles from the vast amount of historical data stored in access logs. In this paper, we define the notion of a ” user session ” and a new distance measure between two web sessions that captures the organization of a web site. A competitive agglomeration clustering algorithm which can automatically cluster data into a parsimonious number of components is used to analyze server access logs and obtain typical session profiles of users. 1