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Fast Quasi-biclique Mining with Giraph

Big Data(2013)

引用 5|浏览4
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摘要
Quasi-biclique mining for bipartite graphs has found important applications in providing security services. However, the standard MapReduce algorithm for mining quasi-bicliques does not scale well due to the need of shuffling and reducing a huge number of map outputs. To cope with web-scale graphs, we propose a scalable algorithm with the use of Giraph, which is a new rising large-scale graph processing platform following the bulk synchronous parallel (BSP) model. Experimental results on real world domain-IP graphs demonstrate that our proposed solution is able to reduce CPU time by 80% and disk I/O by 95%, compared with the standard MapReduce algorithm.
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关键词
Giraph,Bulk Synchronous Parallel,Graph Partitioning,Bipartite Graph,Quasi-Clique
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