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Author:

Qin, Ru-Xin (Qin, Ru-Xin.) | Tian, Ying-Jie (Tian, Ying-Jie.) | Chen, Jing (Chen, Jing.) | Deng, Nai-Yang (Deng, Nai-Yang.) | Zhang, Hai-Bin (Zhang, Hai-Bin.) (Scholars:张海斌)

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Abstract:

In order to make all the association rule algorithms be used for bi-clustering, the bi-cluster problem has been translated into the problem of finding frequent sets in the association rule. With the advent of many algorithms for bi-clustering, the author's technique not only can obtain the bi-clusters, but also can get extra information associated with the bi-cluster. Experimental results on gene expression data show the effectiveness of the strategy.

Keyword:

Data mining Association rules Gene expression Clustering algorithms

Author Community:

  • [ 1 ] [Qin, Ru-Xin]College of Science, China Agricultural University, Beijing 100083, China
  • [ 2 ] [Tian, Ying-Jie]Research Center on Fictitious Economy, Chinese Academy of Sciences, Beijing 100080, China
  • [ 3 ] [Chen, Jing]College of Science, China Agricultural University, Beijing 100083, China
  • [ 4 ] [Deng, Nai-Yang]College of Science, China Agricultural University, Beijing 100083, China
  • [ 5 ] [Zhang, Hai-Bin]College of Applied Sciences, Beijing University of Technology, Beijing 100124, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2009

Issue: 4

Volume: 35

Page: 561-565

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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