A Database-Independent Approach of Mining Association Rules with Genetic Algorithm

UTSePress Research/Manakin Repository

Search UTSePress Research

Advanced Search


My Account

Show simple item record

dc.contributor.author Yan, Xiaowei en_US
dc.contributor.author Zhang, Chengqi en_US
dc.contributor.author Zhang, Shichao en_US
dc.contributor.editor Liu, J; Cheung, Y; Yin, H en_US
dc.date.accessioned 2009-11-09T02:45:19Z
dc.date.available 2009-11-09T02:45:19Z
dc.date.issued 2003 en_US
dc.identifier 2003001856 en_US
dc.identifier.citation Yan Xiaowei, Zhang Chengqi, and Zhang Shichao 2003, 'A Database-Independent Approach of Mining Association Rules with Genetic Algorithm', Springer-Verlag Berlin Heidelberg, Germany, pp. 882-886. en_US
dc.identifier.issn 0302-9743 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/1772
dc.description.abstract Apriori-like algorithms for association rules mining rely upon the minimum support and the minimum confidence. Users often feel hard to give these thresholds. On the other hand, genetic algorithm is effective for global searching, especially when the searching space is so large that it is hardly possible to use deterministic searching method. We try to apply genetic algorithm to the association rules mining and propose an evolutionary method. Computations are conducted, showing that our ARMGA model can be used for the automation of the association rule mining systems, and the ideas given in this paper are effective. en_US
dc.publisher Springer-Verlag Berlin Heidelberg en_US
dc.relation.isbasedon http://dx.doi.org/10.1007/978-3-540-45080-1_123 en_US
dc.title A Database-Independent Approach of Mining Association Rules with Genetic Algorithm en_US
dc.parent Intelligent Data Engineering and Automated learning. 4th International Conference, IDEAL 2003 en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Germany en_US
dc.identifier.startpage 882 en_US
dc.identifier.endpage 886 en_US
dc.cauo.name FEIT.School of Software en_US
dc.conference Verified OK en_US
dc.conference.location Hong Kong, China en_US
dc.for 080109 en_US
dc.personcode 02099760 en_US
dc.personcode 011221 en_US
dc.personcode 020030 en_US
dc.percentage 70 en_US
dc.classification.name Pattern Recognition and Data Mining en_US
dc.classification.type FOR-08 en_US
dc.custom International Conference on Intelligent Data Engineering and Automated Learning en_US
dc.date.activity 20030321 en_US
dc.location.activity Hong Kong, China en_US
dc.description.keywords NA en_US
dc.staffid 020030 en_US

Files in this item

This item appears in the following Collection(s)

Show simple item record