A genetic network programming based method to mine generalized association rules with ontology

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

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

1 Citation (Scopus)

Abstract

In this paper, we propose a Genetic Network Programming based method to mine generalized association rules with 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 Genetic Network Programming (GNP) to mine the rules. Two kinds of fitness functions each with four kinds of policies and a new genetic operator are developed to speed up searching the rule space.

Original languageEnglish
Title of host publicationSICE Annual Conference, SICE 2007
Pages2715-2722
Number of pages8
DOIs
Publication statusPublished - 2007 Dec 1
EventSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan
Duration: 2007 Sep 172007 Sep 20

Publication series

NameProceedings of the SICE Annual Conference

Conference

ConferenceSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
CountryJapan
CityTakamatsu
Period07/9/1707/9/20

Keywords

  • Dynamic threshold approach
  • Generalized association rules
  • Genetic network programming
  • Ontology

ASJC Scopus subject areas

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

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  • Cite this

    Yang, G., Shimada, K., Mabu, S., Hirasawa, K., & Hu, J. (2007). A genetic network programming based method to mine generalized association rules with ontology. In SICE Annual Conference, SICE 2007 (pp. 2715-2722). [4421450] (Proceedings of the SICE Annual Conference). https://doi.org/10.1109/SICE.2007.4421450