Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/42172
DC FieldValue
dc.titleFARMER: Finding interesting rule groups in microarray datasets
dc.contributor.authorCong, G.
dc.contributor.authorTung, A.K.H.
dc.contributor.authorXu, X.
dc.contributor.authorPan, F.
dc.contributor.authorYang, J.
dc.date.accessioned2013-07-04T08:45:10Z
dc.date.available2013-07-04T08:45:10Z
dc.date.issued2004
dc.identifier.citationCong, G.,Tung, A.K.H.,Xu, X.,Pan, F.,Yang, J. (2004). FARMER: Finding interesting rule groups in microarray datasets. Proceedings of the ACM SIGMOD International Conference on Management of Data : 143-154. ScholarBank@NUS Repository.
dc.identifier.issn07308078
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/42172
dc.description.abstractMicroarray datasets typically contain large number of columns but small number of rows. Association rules have been proved to be useful in analyzing such datasets. However, most existing association rule mining algorithms are unable to efficiently handle datasets with large number of columns. Moreover, the number of association rules generated from such datasets is enormous due to the large number of possible column combinations. In this paper, we describe a new algorithm called FARMER that is specially designed to discover association rules from microarray datasets. Instead of finding individual association rules, FARMER finds interesting rule groups which are essentially a set of rules that are generated from the same set of rows. Unlike conventional rule mining algorithms, FARMER searches for interesting rules in the row enumeration space and exploits all user-specified constraints including minimum support, confidence and chi-square to support efficient pruning. Several experiments on real bioinformatics datasets show that FARMER is orders of magnitude faster than previous association rule mining algorithms.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleProceedings of the ACM SIGMOD International Conference on Management of Data
dc.description.page143-154
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.