Quick response data mining model using genetic algorithm

Wenxiang Dou, Takayuki Furuzuki, Kotaro Hirasawa, Gengfeng Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

propose an efficient data mining system for making quick response to users and providing a friendly interface. When data tuples have higher relationship, it could contain long frequent itemsets. If apriori algorithm mines all frequent itemsets in those tuples, its candidate itemsets will become very huge and it has to scan database huge times. Meanwhile, the number of rules mined by the apriori algorithm is huge. Our method avoids mining rules through huge candidate itemsets, just mines maximal frequent itemsets and scans the database for the frequent itemsets users are interested in. First, use GA to mine the maximal frequent itemsets and show them to users. Second, let users pick up one to deduce the association rules. Final, scan the database for the real support and confidence and show them to users. So, our method can not only save many times scanning the database and make quick response to users, but provide a friendly interface that let users select his interesting rules to mine.

Original languageEnglish
Title of host publicationProceedings of the SICE Annual Conference
Pages1214-1219
Number of pages6
DOIs
Publication statusPublished - 2008
EventSICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology - Tokyo
Duration: 2008 Aug 202008 Aug 22

Other

OtherSICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
CityTokyo
Period08/8/2008/8/22

Fingerprint

Data mining
Genetic algorithms
Association rules
Scanning

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications

Cite this

Dou, W., Furuzuki, T., Hirasawa, K., & Wu, G. (2008). Quick response data mining model using genetic algorithm. In Proceedings of the SICE Annual Conference (pp. 1214-1219). [4654843] https://doi.org/10.1109/SICE.2008.4654843

Quick response data mining model using genetic algorithm. / Dou, Wenxiang; Furuzuki, Takayuki; Hirasawa, Kotaro; Wu, Gengfeng.

Proceedings of the SICE Annual Conference. 2008. p. 1214-1219 4654843.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Dou, W, Furuzuki, T, Hirasawa, K & Wu, G 2008, Quick response data mining model using genetic algorithm. in Proceedings of the SICE Annual Conference., 4654843, pp. 1214-1219, SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology, Tokyo, 08/8/20. https://doi.org/10.1109/SICE.2008.4654843
Dou W, Furuzuki T, Hirasawa K, Wu G. Quick response data mining model using genetic algorithm. In Proceedings of the SICE Annual Conference. 2008. p. 1214-1219. 4654843 https://doi.org/10.1109/SICE.2008.4654843
Dou, Wenxiang ; Furuzuki, Takayuki ; Hirasawa, Kotaro ; Wu, Gengfeng. / Quick response data mining model using genetic algorithm. Proceedings of the SICE Annual Conference. 2008. pp. 1214-1219
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