Region of Interest Discovery in Location-Based Social Networking Services with Protected Locations

摘要

Region of Interest (ROI) discovery is one of the most common interests in Location-based social networking services (LBSNS). While former researches mainly utilize the accurate location history, this paper explores the methods to extract those regions with protected locations. A spatial-temporal cloaking check-in model following k-anonymity principle is introduced. And methods to extract two kinds of ROIs, popular regions and personal regions, are proposed respectively. Experimental results illustrate that by analyzing the characteristics of those protected locations, ROIs are able to be discovered as well. Furthermore, our work shows that privacy protection and personalized services can be both achieved in LBSNS.