Genetic Network Programming Based Data Mining Method for Extracting Fuzzy Association Rules
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Taboada:2008:cec,
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author = "Karla Taboada and Eloy Gonzales and Kaoru Shimada and
Kotaro Hirasawa",
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title = "Genetic Network Programming Based Data Mining Method
for Extracting Fuzzy Association Rules",
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booktitle = "2008 IEEE World Congress on Computational
Intelligence",
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year = "2008",
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editor = "Jun Wang",
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pages = "1756--1763",
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address = "Hong Kong",
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month = "1-6 " # jun,
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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isbn13 = "978-1-4244-1823-7",
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file = "EC0434.pdf",
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DOI = "doi:10.1109/CEC.2008.4631027",
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abstract = "In this paper, a new data mining algorithm is proposed
to enhance the capability of exploring interesting
knowledge from databases with continuous values. The
algorithm integrates Fuzzy Set Theory and ``Genetic
Network Programming (GNP)'' to find interesting fuzzy
association rules from given transaction data. GNP is a
novel evolutionary Optimization technique, which uses
directed graph structures as gene instead of strings
(Genetic Algorithms) or trees (Genetic Programming),
contributing to creating quite compact programs and
implicitly memorising past action sequences. We adopt
the Fuzzy Set Theory to mine associate rules that can
be expressed in linguistic terms, which are more
natural and understandable for human beings. The
proposed method can measure the significance of the
extracted association rules using support, confidence
and x2 test,
and obtains a sufficient number of important
association rules in a short time. Experiments
conducted on real world databases are also made to
verify the performances of the proposed method.",
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keywords = "genetic algorithms, genetic programming",
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notes = "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
EPS and the IET.",
- }
Genetic Programming entries for
Karla Taboada
Eloy Gonzales
Kaoru Shimada
Kotaro Hirasawa
Citations