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Journal of Korean Library and Information Science Society

  • P-ISSN2466-2542
  • KCI

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Vol.32 No.3

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The Study on the Effective Automatic Classification of Internet Document Using the Machine Learning

Journal of Korean Library and Information Science Society / Journal of Korean Library and Information Science Society, (P)2466-2542;
2001, v.32 no.3, pp.307-330
노영희
노영희, (2001). The Study on the Effective Automatic Classification of Internet Document Using the Machine Learning. Journal of Korean Library and Information Science Society, 32(3), 307-330.

Abstract

This study experimented the performance of categorization methods using the kNN classifier. Most sample based automatic text categorization techniques like the kNN classifier reduces the feature set of the training documents. We sought to find out which percentage reductions in the feature set would result in high performances. In addition, the kNN classifier has to find the k number of training documents most similar to the test documents in the training documents. We sought to verify the most appropriate k value through experiments.

keywords
Automatic Text Categorization Techniques, kNN Classifier

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