A weight-based feature extraction approach for text classification

Jung Yi Jiang, Shie Jue Lee

研究成果: Conference contribution

4 引文 斯高帕斯(Scopus)

摘要

In this paper, we propose a weight-based feature extraction approach to reduce the number of features for text classification. The number of extracted features is equal to the number of document classes and the feature values are obtained according to the distributions of words over class partitions. Each word of the original word set contributes a weight to each extracted feature and a transformation matrix is formed. By using the transformation matrix, the original document set is converted to a new set with a smaller number of features. The proposed approach has two advantages. Trial-and-error for determining the appropriate number of extracted features can be avoided. Computation demand is small and the method runs fast. Experimental results obtained from real-world data sets have shown that our method can perform better than other methods.

原文English
主出版物標題Second International Conference on Innovative Computing, Information and Control, ICICIC 2007
發行者IEEE Computer Society
ISBN(列印)0769528821, 9780769528823
DOIs
出版狀態Published - 2007 一月 1
事件2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007 - Kumamoto, Japan
持續時間: 2007 九月 52007 九月 7

出版系列

名字Second International Conference on Innovative Computing, Information and Control, ICICIC 2007

Other

Other2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007
國家/地區Japan
城市Kumamoto
期間07-09-0507-09-07

All Science Journal Classification (ASJC) codes

  • 電腦科學(全部)
  • 機械工業

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