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

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@Article{SHIMADAKAORU:20051015,

• 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 Japan",
• year = "2005",
• volume = "46",
• number = "10",
• pages = "2576--2586",
• URL = "http://ci.nii.ac.jp/naid/110002769905/en/",
• month = oct,
• keywords = "genetic algorithms, genetic programming, GNP, Knowledge Processing",
• ISSN = "03875806",
• publisher = "Information Processing Society of Japan (IPSJ)",
• URL = "http://ci.nii.ac.jp/naid/110002769905",
• broken = "http://nels.nii.ac.jp/els/110002769905.pdf?id=ART0003069239&type=pdf&lang=en&host=cinii&order_no=&ppv_type=0&lang_sw=&no=1255721139&cp=",
• 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 \cite{SHIMADAKAORU:2005-10-15}",

}

Genetic Programming entries for Kaoru Shimada Kotaro Hirasawa Jinglu Hu

Citations