Discovery of User Communities from Web Audience Measurement Data

Abstract

As an attempt for discovering Web users of similar tastes, this paper proposes a method for discovering user communities from Web audience measurement data (Web log data). The method is based on an assumption that terms included in an URL often characterize the contents of the Web page pointed by the URL. Complete bipartite graphs are searched from user-term graph obtained from Web audience measurement data without analyzing the contents of Web pages. Experimental results show that our method succeeds in discovering many interesting user communities. Our approach based on graph search, which is common in Web structure mining, is effective also for Web usage mining. Terms attached to discovered user communities can be regarded as labels of the communities, and the terms make manual analysis of the communities easier.