基于区域活跃用户的好友推荐和位置推荐算法

Friends Recommendation and Location Recommendation Algorithm Based on Regional Active Users

针对目前多数基于位置的推荐算法中未考虑用户的实时位置和时间因素,使得推荐缺乏实时性的问题,提出一种基于区域活跃用户的推荐算法,以解决传统基于位置的推荐算法中存在冷启动的问题.首先,发掘用户当前所在位置的区域活跃用户,以此作为推荐标准,为用户进行推荐.其次,在位置推荐中引入时间因素,使推荐更具准确性和实时性.实验结果表明:该算法融入的区域活跃用户好友数可提升推荐系统的实时性;算法融合的位置信息可使推荐更准确.

Aiming at the problem that most of the current location-based recommendation algorithms did not consider the user’s real-time location and time factors,which made the recommendation lack of real-time,we proposed a recommendation algorithm based on regional active users to solve the cold start problem in traditional location-based recommendation algorithm.Firstly,the algorithm explored the active user in the area where the user was currently located,and used this as a standard to recommend for the user.Secondly,time factor was introduced into location recommendation to make the recommendationmore accurate and real-time.The experimental results show that the number of active user’s friends in the algorithm can improve the real-time performance ofthe recommendation system,and the fusion of location information in the algorithm can make the recommendation more accurate.