Individual location recommendation for location-based social network

被引：0
作者：
Xu, Ya-Bin [1 ,2 ]
Sun, Xiao-Chen [1 ]
机构：
[1] School of Computer, Beijing Information Science and Technology University, Beijing
[2] Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing
来源：
Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications | 2015年 / 38卷 / 05期
关键词：
Collaborative filtering; Individual location recommendation; Location-based service; Location-based social network;
D O I：
10.13190/j.jbupt.2015.05.023
中图分类号：
学科分类号：
摘要：
In order to effectively improve the users' experience for location social networks, a model of personalized location recommendation service was proposed. Considering the users' check-in behavior features, the users' characteristics and semantic features of interested location point, this model combines the ant colony algorithm with the improved hybrid collaborative filtering algorithm to improve the quality and efficiency of the individual location recommendation. Experiments show that, the recall, accuracy and average absolute error value of the location recommendation model proposed in this article is superior to the existing methods. © 2015, Beijing University of Posts and Telecommunications. All right reserved.
引用
收藏
页码：118 / 124
页数：6
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