兴趣点推荐方法研究综述

Point-of-interest Recommendation:A Survey

兴趣点(Point-Of-Interest,POI)推荐是基于位置的社交网络(Location-Based Social Networks,LBSN)中一项重要的服务,无论对商家还是对客户都有重要的影响,并且兴趣点数据作为时空数据的典型更是得到了广泛关注,因此兴趣点推荐近年来已经成为学术界的热门研究课题。文章分析了兴趣点推荐的影响因素,对传统兴趣点推荐方法进行了总结,分析了最新的基于图嵌入方法以及图神经网络在兴趣点推荐领域中的应用,最后对兴趣点推荐所面临的挑战以及未来的研究趋势加以分析。

Point-of-interest(POI)recommendation is an important service in location-based social networks(LBSN),which has an important impact on both merchants and customers.As a typical example of spatio-temporal data,POI recommendation has been widely concerned,so it has become a hot research topic in academic circles in recent years.This paper analyzes the influencing factors of interest point recommendation,summarizes the traditional methods of interest point recommendation,the latest graph-based embedding methods and the application of graph neural networks in the field of point-of-interest recommendation are analyzed.Finally,it analyzes the challenges faced by points of interest recommendation and future research trends.