关键词: 社交网络, 轨迹, 用户亲密度, 位置信息, 聚类

Abstract: This paper presents a new clustering algorithm for Location-based Social-network Hot Trajectory（LSHT）, which combines social network characteristics into the location-based hot trajectory discovery. The algorithm introduces friendship intimacy and friendship activeness to analyze the relationship among users. Meanwhile, the algorithm introduces a ranking function for hot trajectory based on calculating the influence of the users’ trajectories. Combining friendship intimacy and ranking function, the algorithm digs out the hot trajectory from friends’ trajectories by filtering out the fake trajectories. The experiments show the LSHT can accurately and effectively discover the hot trajectory in a location-based social network.

Key words: social network, trajectory, friendship intimacy, location information, clustering