Design and evaluation of a user-based community discovery technique

Common experience suggests that users of online services can be grouped into communities on the basis of interest Much of the recent research on algorithms for identification of communities in the Web has focused on techniques that rely on link structures. In this paper, we describe a new technique for discovering communities of interest in Web services. Instead of relying upon link structures, we propose an algorithm based on user access behavior. We create a graph, based on the user access patterns and show that it has useful properties for community discovery. We apply our algorithm to a synthetic dataset, known to show interest-based community structure, and use the results to compare our algorithm against other methodologies. We also apply the algorithm to two real world online services: a bookstore and an online radio. The case studies are relevant because they emphasize the contribution of the algorithm to find out communities in an environment without explicit structures that represent relationships among users.