Comparative Association Rules Mining Using Genetic Network Programming (GNP) with Attributes Accumulation Mechanism and its Application to Traffic Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Wei:2008:cec,

• author = "Wei Wei and Huiyu Zhou and Kaoru Shimada and Shingo Mabu and Kotaro Hirasawa",
• title = "Comparative Association Rules Mining Using Genetic Network Programming (GNP) with Attributes Accumulation Mechanism and its Application to Traffic Systems",
• booktitle = "2008 IEEE World Congress on Computational Intelligence",
• year = "2008",
• editor = "Jun Wang",
• pages = "292--298",
• address = "Hong Kong",
• month = "1-6 " # jun,
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• isbn13 = "978-1-4244-1823-7",
• file = "EC0090.pdf",
• DOI = "doi:10.1109/CEC.2008.4630813",
• abstract = "In this paper, we present a method of comparative association rules mining using Genetic Network Programming (GNP) with attributes accumulation mechanism in order to uncover association rules between different datasets. GNP is an evolutionary approach which can evolve itself and find the optimal solutions. The motivation of the comparative association rules mining method is to use the data mining approach to check two or more databases instead of one, so as to find the hidden relations among them. The proposed method measures the importance of association rules by using the absolute difference of confidences among different databases and can get a number of interesting rules. Association rules obtained by comparison can help us to find and analyse the explicit and implicit patterns among a large amount of data. For the large attributes case, the calculation is very time-consuming, when the conventional GNP based data mining is used. So, we have proposed an attribute accumulation mechanism to improve the performance. Then, the comparative association rules mining using GNP has been applied to a complicated traffic system. By mining and analysing the rules under different traffic situations, it was found that we can get interesting information of the traffic system.",
• keywords = "genetic algorithms, genetic programming",
• notes = "WCCI 2008 - A joint meeting of the IEEE, the INNS, the EPS and the IET.",

}

Genetic Programming entries for Wei Wei Huiyu Zhou Kaoru Shimada Shingo Mabu Kotaro Hirasawa

Citations