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Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/41486
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dc.titleMining frequent closed patterns in microarray data
dc.contributor.authorCong, G.
dc.contributor.authorTan, K.-L.
dc.contributor.authorTung, A.K.H.
dc.contributor.authorPan, F.
dc.date.accessioned2013-07-04T08:28:40Z
dc.date.available2013-07-04T08:28:40Z
dc.date.issued2004
dc.identifier.citationCong, G.,Tan, K.-L.,Tung, A.K.H.,Pan, F. (2004). Mining frequent closed patterns in microarray data. Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004 : 363-366. ScholarBank@NUS Repository.
dc.identifier.isbn0769521428
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41486
dc.description.abstractMicroarray 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 new algorithms that explore the row enumeration space to mine frequent closed patterns. Several experiments on real-life gene expression data show that the new algorithms are faster than existing algorithms, including CLOSET, CHARM, CLOSET+ and CARPENTER. © 2004 IEEE.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleProceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
dc.description.page363-366
dc.identifier.isiutNOT_IN_WOS
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