Rough set model for discovering single-dimensional and multidimensional association rules

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dc.contributor.author Ma, Xin en_US
dc.contributor.author Ma, Jun en_US
dc.contributor.editor NA en_US
dc.date.accessioned 2010-06-16T05:00:11Z
dc.date.available 2010-06-16T05:00:11Z
dc.date.issued 2004 en_US
dc.identifier 2009005266 en_US
dc.identifier.citation Ma Xin and Ma Jun 2004, 'Rough set model for discovering single-dimensional and multidimensional association rules', IEEE, Piscatawy, USA, pp. 3531-3536. en_US
dc.identifier.issn 0-7803-8566-7 en_US
dc.identifier.other E1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/11941
dc.description.abstract In this paper, the mining of association rules with rough set technology is investigated as the algorithm RSASM. The RSASM algorithm is introduced for mining of single-dimensional association rules, which is constituted of three steps: (1) generalizing database to discretize quantitative attributes and decrease quantity of data; (2) finding candidate itemsets with the concept of equivalence class derived from indiscernibility relation in rough set theory; and (3) finding frequent itemsets with multiple minimum supports. The RSASM can be expanded to multidimensional association rules mining easily. It can be seen from experiments that the mining algorithm is elegant and efficient, which can obtain more rapid computing speed and sententious rules at the same time. en_US
dc.language en_US
dc.publisher IEEE en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/ICSMC.2004.1400889 en_US
dc.title Rough set model for discovering single-dimensional and multidimensional association rules en_US
dc.parent Proceedings of 2004 IEEE International Conference on Systems, Man and Cybernetics en_US
dc.journal.volume 4 en_US
dc.journal.number en_US
dc.publocation Piscatawy, USA en_US
dc.identifier.startpage 3531 en_US
dc.identifier.endpage 3536 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 080600 en_US
dc.personcode 0000062252 en_US
dc.personcode 999403 en_US
dc.percentage 100 en_US
dc.classification.name Information Systems en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom IEEE Conference on Systems, Man and Cybernetics en_US
dc.date.activity 20041010 en_US
dc.location.activity The Hague, Netherlands en_US
dc.description.keywords data mining , database management systems , rough set theory en_US
dc.staffid en_US
dc.staffid 999403 en_US


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