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[ACM Press the 1st International Workshop - Beijing, China (2012.08.12-2012.08.12)] Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining Algorithms, Systems, Programming Models and Applications - BigMine '12 - Online feature selection for mining big data

โœ Scribed by Hoi, Steven C. H.; Wang, Jialei; Zhao, Peilin; Jin, Rong

Book ID
125450881
Publisher
ACM Press
Year
2012
Weight
710 KB
Category
Article
ISBN
145031547X

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[ACM Press the 1st International Worksho
[ACM Press the 1st International Workshop - Beijing, China (2012.08.12-2012.08.12)] Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining Algorithms, Systems, Programming Models and Applications - BigMine '12 - A parallel graph partitioning algorithm to speed up the large-scale distributed graph mining
โœ Zeng, ZengFeng; Wu, Bin; Wang, Haoyu ๐Ÿ“‚ Article ๐Ÿ“… 2012 ๐Ÿ› ACM Press โš– 730 KB
[ACM Press the 1st International Worksho
[ACM Press the 1st International Workshop - Beijing, China (2012.08.12-2012.08.12)] Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining Algorithms, Systems, Programming Models and Applications - BigMine '12 - A parallel graph partitioning algorithm to speed up the large-scale distributed graph mining
โœ Zeng, ZengFeng; Wu, Bin; Wang, Haoyu ๐Ÿ“‚ Article ๐Ÿ“… 2012 ๐Ÿ› ACM Press โš– 730 KB

For the large-scale distributed graph mining, the graph is distributed over a cluster of nodes, thus performing computations on the distributed graph is expensive when large amount of data have to be moved between different computers. A good partitioning of distributed graph is needed to reduce the