A Rule Generation Technique Utilizing a Parallel Expansion Method


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 5, No. 4, pp. 942-950, Apr. 1998
10.3745/KIPSTE.1998.5.4.942,   PDF Download:

Abstract

Extraction of knowledge, expecially in the form of rules, from raw data is very important in data mining, the aim of which is to help users who feel the lack of knowledge in spite of the abundance of data. Logic minimization tools are ones which derive optimized knowledge given ON set and DC set. First, the parallel expansion scheme of logic minimization is extracted and used to obtain initial knowledge. Then sorting, reduction, and rule expansion schemes are designed and applied to the initial knowledge to get final rules, which are successfully applicable to real world data. The prototype system based on this new approach has been experimented with real world data to show that it is as practical as conventional long studied decision tree methods like C4.5 system.


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Cite this article
[IEEE Style]
L. K. Cheol and K. J. Bong, "A Rule Generation Technique Utilizing a Parallel Expansion Method," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 5, no. 4, pp. 942-950, 1998. DOI: 10.3745/KIPSTE.1998.5.4.942.

[ACM Style]
Lee Kee Cheol and Kim Jin Bong. 1998. A Rule Generation Technique Utilizing a Parallel Expansion Method. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 5, 4, (1998), 942-950. DOI: 10.3745/KIPSTE.1998.5.4.942.