Online Extracting Sessions of Frequent Users

Web usage mining aims to discover interesting user access patterns from the data derived from interactions of users. The primary source data for web usage mining approach is user sessions extracted from web server logs. However, logs are usually very large and contain sessions of users with different behaviors. To expedite mining processes and enhance mining results, we consider extracting sessions of frequent users. In this paper, we investigate the problem of finding all frequent users as well as obtaining their sessions. Instead of discovering frequent users over static web log files, we present an online algorithm named FUSMiner to solve the mining task in a streaming environment. The experimental results show that our proposed algorithm is both efficient and effective.