期刊
2018 IEEE 34TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE)
卷 -, 期 -, 页码 233-244出版社
IEEE
DOI: 10.1109/ICDE.2018.00030
关键词
-
资金
- NSFC [61672235, DP170101628, DP180103096]
- ARC [DP180103096, DP160101513]
Driven by real-life applications in geo-social networks, in this paper, we investigate the problem of computing the radius-bounded k-cores (RB-k-cores) that aims to find cohesive subgraphs satisfying both social and spatial constraints on large geo-social networks. In particular, we use k-core to ensure the social cohesiveness and we use a radius-bounded circle to restrict the locations of users in a RB-k-core. We explore several algorithmic paradigms to compute RB-k-cores, including a triple-vertex-based paradigm, a binary-vertex-based paradigm, and a paradigm utilizing the concept of rotating circles. The rotating-circle-based paradigm is further enhanced with several pruning techniques to achieve better efficiency. The experimental studies conducted on both real and synthetic datasets demonstrate that our proposed rotating-circle-based algorithms can compute all RB-k-cores very efficiently. Moreover, it can also be used to compute the minimum-circle-bounded k-core and significantly outperforms the existing techniques for computing the minimum-circle-bounded k-core.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据