Abstract: With the widespread of smart terminals such as smart phones and smart pads, using MAC address as user identification in campus wireless local area network (WLAN) user clustering research cannot exactly represent user behavior. An user filtering based user clustering is proposed. This method filters users’ behavior data by their degree of activeness, and then further conducts clustering analysis of campus WLAN user behavior. The experimental result verifies the effectiveness of the proposed method.