Cart (Loading....) | Create Account
Close category search window
 

Genetic Network Programming with Acquisition Mechanisms of Association Rules in Dense Database

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Shimada, K. ; Graduate Sch. of Inf., Production & Syst., Waseda Univ., Fukuoka ; Hirasawa, K. ; Jinglu Hu

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 a priori-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

Published in:

Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on  (Volume:2 )

Date of Conference:

28-30 Nov. 2005

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.