吉林大学学报(理学版) ›› 2018, Vol. 56 ›› Issue (6): 1441-1446.

• 计算机科学 • 上一篇    下一篇

基于区域活跃用户的好友推荐和位置推荐算法

董立岩1, 王雪松1, 王朝阳1, 李永丽2   

  1. 1. 吉林大学 计算机科学与技术学院, 长春 130012; 2. 东北师范大学 信息科学与技术学院, 长春 130117
  • 收稿日期:2018-07-02 出版日期:2018-11-26 发布日期:2018-11-26
  • 通讯作者: 董立岩 E-mail:dongly@jlu.edu.cn

Friends Recommendation and Location RecommendationAlgorithm Based on Regional Active Users#br#

DONG Liyan1, WANG Xuesong1, WANG Zhaoyang1, LI Yongli2   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;2. School of Information Science and Technology, Northeast Normal University, Changchun 130117, China
  • Received:2018-07-02 Online:2018-11-26 Published:2018-11-26

摘要: 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.

关键词: 区域活跃用户, 推荐算法, 好友推荐, 位置推荐, 实时性

Abstract: 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 recommendation more 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 of the recommendation system, and the fusion of location information in the algorithm can make the recommendation more accurate.

Key words: regional active user, recommendation algorithm, friend recommendation, location recommendation, realtime

中图分类号: 

  • TP181