Genetic network programming with acquisition mechanisms of association rules in dense database

Kaoru Shimada, Kotaro Hirasawa, Takayuki Furuzuki

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

5 Citations (Scopus)

Abstract

A method of association rule mining using Genetic Network Programming (GNP) is proposed to improve the performance of association rule extraction from dense database. Rule extraction is done without identifying frequent itemsets used in Apriori-like methods. Association rules are represented as the connections of nodes in GNP. The proposed mechanisms calculate measurements of association rules directly from a database using GNP, and measure the significance of the association via the chi-squared test. The proposed system evolves itself by an evolutionary method and obtains candidates of association rules by genetic operations. Extracted association rules are stored in a pool all together through generations and reflected in genetic operators as acquired information. In this paper, we describe an algorithm capable of finding important association rules using GNP with sophisticated rule acquisition mechanisms and present some experimental results.

Original languageEnglish
Title of host publicationProceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet
Pages47-54
Number of pages8
Volume2
Publication statusPublished - 2005
EventInternational Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, IAWTIC 2005 - Vienna
Duration: 2005 Nov 282005 Nov 30

Other

OtherInternational Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, IAWTIC 2005
CityVienna
Period05/11/2805/11/30

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Association rules

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Shimada, K., Hirasawa, K., & Furuzuki, T. (2005). Genetic network programming with acquisition mechanisms of association rules in dense database. In Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet (Vol. 2, pp. 47-54). [1631444]

Genetic network programming with acquisition mechanisms of association rules in dense database. / Shimada, Kaoru; Hirasawa, Kotaro; Furuzuki, Takayuki.

Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet. Vol. 2 2005. p. 47-54 1631444.

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

Shimada, K, Hirasawa, K & Furuzuki, T 2005, Genetic network programming with acquisition mechanisms of association rules in dense database. in Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet. vol. 2, 1631444, pp. 47-54, International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, IAWTIC 2005, Vienna, 05/11/28.
Shimada K, Hirasawa K, Furuzuki T. Genetic network programming with acquisition mechanisms of association rules in dense database. In Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet. Vol. 2. 2005. p. 47-54. 1631444
Shimada, Kaoru ; Hirasawa, Kotaro ; Furuzuki, Takayuki. / Genetic network programming with acquisition mechanisms of association rules in dense database. Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet. Vol. 2 2005. pp. 47-54
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