Mining equalized association rules from multi concept layers of ontology using Genetic Network Programming

Guangfei Yang, Kaoru Shimada, Shingo Mabu, Kotaro Hirasawa, Jinglu Hu

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

9 Citations (Scopus)

Abstract

In this paper, we propose a Genetic Network Programming based method to mine equalized association rules in multi concept layers of ontology. We first introduce ontology to facilitate building the multi concept layers and propose Dynamic Threshold Approach (DTA) to equalize the different layers. We make use of an evolutionary computation method called Genetic Network Programming (GNP) to mine the rules and develop a new genetic operator to speed up searching the rule space. The simulation results show that our method could efficiently find some rules even in the early generations.

Original languageEnglish
Title of host publication2007 IEEE Congress on Evolutionary Computation, CEC 2007
Pages705-712
Number of pages8
DOIs
Publication statusPublished - 2007 Dec 1
Event2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore
Duration: 2007 Sep 252007 Sep 28

Publication series

Name2007 IEEE Congress on Evolutionary Computation, CEC 2007

Conference

Conference2007 IEEE Congress on Evolutionary Computation, CEC 2007
CountrySingapore
Period07/9/2507/9/28

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

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  • Cite this

    Yang, G., Shimada, K., Mabu, S., Hirasawa, K., & Hu, J. (2007). Mining equalized association rules from multi concept layers of ontology using Genetic Network Programming. In 2007 IEEE Congress on Evolutionary Computation, CEC 2007 (pp. 705-712). [4424540] (2007 IEEE Congress on Evolutionary Computation, CEC 2007). https://doi.org/10.1109/CEC.2007.4424540