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
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