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2009
ACM

Parallel community detection on large networks with propinquity dynamics

8 years 9 months ago
Parallel community detection on large networks with propinquity dynamics
Graphs or networks can be used to model complex systems. Detecting community structures from large network data is a classic and challenging task. In this paper, we propose a novel community detection algorithm, which utilizes a dynamic process by contradicting the network topology and the topology-based propinquity, where the propinquity is a measure of the probability for a pair of nodes involved in a coherent community structure. Through several rounds of mutual reinforcement between topology and propinquity, the community structures are expected to naturally emerge. The overlapping vertices shared between communities can also be easily identified by an additional simple postprocessing. To achieve better efficiency, the propinquity is incrementally calculated. We implement the algorithm on a vertex-oriented bulk synchronous parallel(BSP) model so that the mining load can be distributed on thousands of machines. We obtained interesting experimental results on several real network d...
Yuzhou Zhang, Jianyong Wang, Yi Wang, Lizhu Zhou
Added 26 Jul 2010
Updated 26 Jul 2010
Type Conference
Year 2009
Where KDD
Authors Yuzhou Zhang, Jianyong Wang, Yi Wang, Lizhu Zhou
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