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http://dx.doi.org/10.5391/JKIIS.2004.14.2.142

Automatic Determination of Usenet News Groups from User Profile  

Kim, Jong-Wan (대구대학교 컴퓨터ㆍIT공학부)
Cho, Kyu-Cheol (대구대학교 컴퓨터ㆍIT공학부)
Kim, Hee-Jae (대구대학교 컴퓨터ㆍIT공학부)
Kim, Byeong-Man (금오공과대학교 컴퓨터공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.14, no.2, 2004 , pp. 142-149 More about this Journal
Abstract
It is important to retrieve exact information coinciding with user's need from lots of Usenet news and filter desired information quickly. Differently from email system, we must previously register our interesting news group if we want to get the news information. However, it is not easy for a novice to decide which news group is relevant to his or her interests. In this work, we present a service classifying user preferred news groups among various news groups by the use of Kohonen network. We first extract candidate terms from example documents and then choose a number of representative keywords to be used in Kohonen network from them through fuzzy inference. From the observation of training patterns, we could find the sparsity problem that lots of keywords in training patterns are empty. Thus, a new method to train neural network through reduction of unnecessary dimensions by the statistical coefficient of determination is proposed in this paper. Experimental results show that the proposed method is superior to the method using every dimension in terms of cluster overlap defined by using within cluster distance and between cluster distance.
Keywords
Usenet news filtering; fuzzy inference; Kohonen network; statistical coefficient of determination; dimensionality reduction;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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