DocumentCode :
2850761
Title :
Mining frequent closed patterns in microarray data
Author :
Cong, Gao ; Tan, Kian-Lee ; Tung, Anthony K H ; Pan, Feng
Author_Institution :
Sch. of Comput., Singapore Nat. Univ., Singapore
fYear :
2004
fDate :
1-4 Nov. 2004
Firstpage :
363
Lastpage :
366
Abstract :
Microarray data typically contains a large number of columns and a small number of rows, which poses a great challenge for existing frequent (closed) pattern mining algorithms that discover patterns in item enumeration space. In this paper, we propose two algorithms that explore the row enumeration space to mine frequent closed patterns. Several experiments on real-life gene expression data show that the algorithms are faster than existing algorithms, including CLOSET, CHARM, CLOSET+ and CARPENTER.
Keywords :
data mining; spatial data structures; frequent closed pattern mining; item enumeration space; microarray data; pattern discovery; real-life gene expression data; row enumeration space; Association rules; Data mining; Databases; Drives; Gene expression; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, 2004. ICDM '04. Fourth IEEE International Conference on
Print_ISBN :
0-7695-2142-8
Type :
conf
DOI :
10.1109/ICDM.2004.10070
Filename :
1410311
Link To Document :
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