The rapid spreading of mobile devices and smartphones has promoted the deployment of enterprise WLANs. This research collects read traces from over 10000 WiFi users in one university in Shanghai. Through intensive data analysis, it finds that there exists more than 24% redundancy traffic in WLANs. By mining the patterns of data set, a user-oriented redundancy elimination strategy is proposed to allocate different cache sizes to different users adaptively. Simulation results show that user-oriented redundancy elimination strategy can detect and eliminate redundant traffic effectively.