Data Mining Using Genetic Network Programming with the Use of Acquired Information

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Kaoru Shimada and Kotaro Hirasawa and 
                 Takayuki Furuzuki",
  title =        "Data Mining Using Genetic Network Programming with the
                 Use of Acquired Information",
  journal =      "Transactions of Information Processing Society of
  year =         "2005",
  volume =       "46",
  number =       "10",
  pages =        "2576--2586",
  URL =          "",
  month =        oct,
  keywords =     "genetic algorithms, genetic programming, GNP,
                 Knowledge Processing",
  ISSN =         "03875806",
  publisher =    "Information Processing Society of Japan (IPSJ)",
  URL =          "",
  broken =       "",
  size =         "11 pages",
  abstract =     "A method of association rule mining using Genetic
                 Network Programming (GNP) is proposed to improve the
                 performance of rule extraction. The proposed system
                 evolves itself by an evolutionary method and measures
                 the significance of the association via the chi-squared
                 test using GNP. Extracted association rules are stored
                 in a pool all together through generations in order to
                 find new important rules. These rules are reflected in
                 genetic operators as acquired information. Therefore,
                 the proposed method is fundamentally different from all
                 other evolutionary methods in its evolutionary way. In
                 this paper, we describe the algorithm capable of
                 finding the important association rules and present
                 some experimental results.",
  notes =        "In Japanese. Also known as

Genetic Programming entries for Kaoru Shimada Kotaro Hirasawa Jinglu Hu