兴趣点推荐系统研究综述

A Survey of Point-of-Interest Recommender System

基于位置的社交网络在日常生活中的应用逐渐增加,如何帮助用户进行出行规划已成为诸多服务的关注点,兴趣点推荐系统因而成为研究热点之一.目前已有的兴趣点推荐系统利用地理位置、签到序列、社交关系、地点属性等影响因素,通过基于协同过滤的推荐框架及基于联合模型的推荐框架等推荐方法进行兴趣点推荐.在已有兴趣点推荐研究的基础上,深度学习的应用与情境兴趣点推荐可能成为新的研究方向.

The application of location-based social network in daily life is increasing gradually.How to help users to plan their travels has become the focus of many services,and the Point-of-Interest(POI)recommender system has become one of the research hotspots.The existing POI recommendation systems use geographical location,check-in sequence,social relationship,location attribute and other factors to recommend the POIs through the recommendation framework based on collaborative filtering and the recommendation framework based on joint model.Based on the existing research,the application of deep learning and the situation recommendation of POI may become new research directs.