关键词: 基于位置社交网络, 兴趣点推荐, 动态异构网络, 时间感知, 矩阵分解

Abstract:

With the rapid development of Location-Based Social Network（LBSN）, Point-Of-Interest（POI） recommendation can help people to discover interesting and attractive locations. Facing the challenging problems in LBSN, such as the sparseness of data and dynamics of user interest, it proposes the method of time-aware point-of-interest recommendation based on dynamic heterogeneous network in LBSN in this paper. Firstly, the session node type is added into the network schema in LBSN. The time information, position information and social information are integrated into the semantic relation between the user and POI by the dynamic meta-path. Secondly, the set of dynamic meta-path between user and POI is given, and the computational method of preference degree of dynamic path instances is proposed. Thirdly, the dynamic preference matrixes are factorized by the method of matrix factorization model. Finally, the POI recommendation list of user can be obtained at target time slot by the user feature matrixes and POI feature matrixs of different dynamic meta-paths. The experimental results show that the proposed method gets the best recommendation results in the aspect of precision of POI recommendation compared to other POI recommendation methods, and has a good application prospect.

Key words: location-based social network, Point-Of-Interest（POI） recommendation, dynamic heterogeneous network, time-aware, matrix factorization