Abstract: Clustering Web documents is a fundamental task in Web Mining. Clustering analysis assists in reducing search space and decreasing information retrieval time. In this study we present a new data model for Web document representation based on granulation computing, named as Expanded Vector Space Model (EVSM), which facilitates knowledge engineers to acquire and understand processing results. We experimentally evaluate the proposed approach and demonstrate that our algorithm is promising and efficient.