STUN: Spatio-Temporal Uncertain (Social) Networks

被引:1
|
作者
Kang, Chanhyun [1 ]
Pugliese, Andrea [2 ]
Grant, John [1 ]
Subrahmanian, V. S. [1 ]
机构
[1] Univ Maryland, Dept Comp Sci, College Pk, MD 20742 USA
[2] Univ Calabria, DEIS Dept, I-87030 Commenda Di Rende, Italy
关键词
D O I
10.1109/ASONAM.2012.93
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
STUN is an extension of social networks in which the edges are characterized by spatio-temporal annotations, as well as uncertainty allowing us to express not only relationships between vertices, but when and where these relationships were true, and how certain we are that the relationships hold. We propose a STUN query language that consists of subgraphs with spatio-temporal constraints and uncertainty requirements. We then develop an index structure to store STUN graphs, together with an algorithm to answer such queries. We describe experiments with a real-world YouTube social network data set and show that our algorithm performs well on graphs with over a million edges.
引用
收藏
页码:543 / 550
页数:8
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