Social network discovery by mining spatio-temporal events

被引:29
作者
Lauw H.W. [1 ]
Lim E.-P. [1 ]
Pang H. [2 ]
Tan T.-T. [3 ]
机构
[1] School of Computer Engineering, Nanyang Technological University, Singapore 639798, Nanyang Avenue
[2] School of Information Systems, Singapore Management University, Singapore 178902
[3] Centre for IT Services, Nanyang Technological University, Singapore 639798, Nanyang Avenue
关键词
Data mining; Pattern discovery; Spatio-temporal analysis;
D O I
10.1007/s10588-005-3939-9
中图分类号
学科分类号
摘要
Knowing patterns of relationship in a social network is very useful for law enforcement agencies to investigate collaborations among criminals, for businesses to exploit relationships to sell products, or for individuals who wish to network with others. After all, it is not just what you know, but also whom you know, that matters. However, finding out who is related to whom on a large scale is a complex problem. Asking every single individual would be impractical, given the huge number of individuals and the changing dynamics of relationships. Recent advancement in technology has allowed more data about activities of individuals to be collected. Such data may be mined to reveal associations between these individuals. Specifically, we focus on data having space and time elements, such as logs of people's movement over various locations or of their Internet activities at various cyber locations. Reasoning that individuals who are frequently found together are likely to be associated with each other, we mine from the data instances where several actors co-occur in space and time, presumably due to an underlying interaction. We call these spatio-temporal co-occurrences events, which we use to establish relationships between pairs of individuals. In this paper, we propose a model for constructing a social network from events, and provide an algorithm that mines these events from the data. Experiments on a real-life data tracking people's accesses to cyber locations have also yielded encouraging results. © 2005 Springer Science + Business Media, Inc.
引用
收藏
页码:97 / 118
页数:21
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