Web News Classification Using Neural Networks Based on PCA

DOI
  • Selamat Ali
    Division of Computer and Systems Sciences, Engineering Department, Osaka Prefecture University
  • Yanagimoto Hidekazu
    Division of Computer and Systems Sciences, Engineering Department, Osaka Prefecture University
  • Omatu Sigeru
    Division of Computer and Systems Sciences, Engineering Department, Osaka Prefecture University

Description

In this paper, we propose a news web page classification method (WPCM). The WPCM uses a neural network with inputs obtained by both the principal components and class profile-based features (CPBF). The fixed number of regular words from each class will be used as a feature vectors with the reduced features from the PCA. These feature vectors are then used as the input to the neural networks for classification. The experimental evaluation demonstrates that the WPCM provides acceptable classification accuracy with the sports news datasets.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390282680562184832
  • NII Article ID
    130006960387
  • DOI
    10.11499/sicep.2002.0.526.0
  • Text Lang
    en
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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