DocumentCode :
3006971
Title :
Fast Quasi-biclique Mining with Giraph
Author :
Hsiao-Fei Liu ; Chung-Tsai Su ; An-Chiang Chu
Author_Institution :
CoreTech, Trend Micro, Inc., Taipei, Taiwan
fYear :
2013
fDate :
June 27 2013-July 2 2013
Firstpage :
347
Lastpage :
354
Abstract :
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.
Keywords :
Internet; data mining; parallel algorithms; security of data; BSP model; Giraph; MapReduce algorithm; Web-scale graphs; bipartite graphs; bulk synchronous parallel model; domain-IP graphs; fast quasi-biclique mining; large-scale graph processing platform; security services; Algorithm design and analysis; Bipartite graph; Communities; Data mining; Partitioning algorithms; Servers; Standards; Bipartite Graph; Bulk Synchronous Parallel; Giraph; Graph Partitioning; Quasi-Clique;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data (BigData Congress), 2013 IEEE International Congress on
Conference_Location :
Santa Clara, CA
Print_ISBN :
978-0-7695-5006-0
Type :
conf
DOI :
10.1109/BigData.Congress.2013.53
Filename :
6597157
Link To Document :
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