Local Community Identification through User Access Patterns

TL;DR

This paper introduces a novel local community detection method based on user access patterns from server logs, focusing on user behavior rather than traditional link-based relationships, with applications demonstrated on online services.

Contribution

It presents a new algorithm for community detection that relies on user access data instead of author-imposed links, applicable to environments like streaming media without explicit links.

Findings

Effective identification of user communities in non-link environments

Application to online bookstore and radio services

Highlights the algorithm's ability to reveal communities without hyperlinks

Abstract

Community identification algorithms have been used to enhance the quality of the services perceived by its users. Although algorithms for community have a widespread use in the Web, their application to portals or specific subsets of the Web has not been much studied. In this paper, we propose a technique for local community identification that takes into account user access behavior derived from access logs of servers in the Web. The technique takes a departure from the existing community algorithms since it changes the focus of in terest, moving from authors to users. Our approach does not use relations imposed by authors (e.g. hyperlinks in the case of Web pages). It uses information derived from user accesses to a service in order to infer relationships. The communities identified are of great interest to content providers since they can be used to improve quality of their services. We also propose an evaluation methodology for analyzing the results obtained by the algorithm. We present two case studies based on actual data from two services: an online bookstore and an online radio. The case of the online radio is particularly relevant, because it emphasizes the contribution of the proposed algorithm to find out communities in an environment (i.e., streaming media service) without links, that represent the relations imposed by authors (e.g. hyperlinks in the case of Web pages).