关键词: 位置社交网络, 兴趣点推荐, 协同过滤

Abstract: The existing point of interest recommendation algorithm based on the collaborative filtering can obtain good effect, but when users are far away from their residence, the recommend effect has fallen sharply. The main reason is that user’s check-ins mainly concentrate around its residence, and has less activity history in other locations, which results in not accurately calculating the user interest at this time. This paper proposes a point of interest recommendation method based on topic model, which can give consideration to both personal interest and point of interest’s preference in order to get satisfactory recommendation lists in a new city. Experiments show that the methods can not only ease data sparseness problem to a certain extent, but also outperform other methods.

Key words: location-based social networks, location recommendation, collaborative filtering