User Behavior Analysis of Location-based Social Network

被引：3
|
作者：
Zeng, Jun [1 ]
He, Xin [2 ]
Wu, Yingbo [2 ]
Hirokawa, Sachio [3 ]
机构：
[1] Sch Big Data & Software Engn, Key Lab Dependable Serv Comp Cyber Phys Soc, Chongqing, Peoples R China
[2] Sch Big Data & Software Engn, Chongqing, Peoples R China
[3] Kyushu Univ, Res Inst Informat Technol, Fukuoka, Fukuoka, Japan
来源：
2018 7TH INTERNATIONAL CONGRESS ON ADVANCED APPLIED INFORMATICS (IIAI-AAI 2018) | 2018年
基金：
中国国家自然科学基金;
关键词：
user behavior; behavioral analysis; next location prediction; LBSN;
D O I：
10.1109/IIAI-AAI.2018.00015
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
User behavior changes over time under the influence of their activities. We contend that these activities are non-random behavior and have a desire to explore the underlying information behind these changes. In this paper, we analyze user behavior by using the check-in data in Location Based Social Networks (LBSNs), and examine whether they have the features of trend, periodicity and surprise or not. We explore some dynamics behaviors of people through their check-in times, and divide time into annually, monthly and even weekly analysis to find out the pattern of their behavior. Eventually, we found the check-in data do exhibit these three features by analyzing them deeply. The analytical work lays the foundation for the further recommendation research.
引用
收藏
页码：21 / 25
页数：5
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