Hierarchical fuzzy-KNN networks for news documents categorization

Jung Hsien Chiang, Yan Cheng Chen

研究成果: Paper同行評審

5 引文 斯高帕斯(Scopus)

摘要

In this paper, we present a document categorization method based on the hierarchical fuzzy networks. The proposed model employs the divide-and-conquer principle to resolve documents categorization problem based on a predefined hierarchical structure. The final classification framework can be interpreted as a hierarchical array of non-linear decision tree. Each node in the tree represents one filter. The fuzzy K-nearest-neighbor (KNN)-based filter decides that the unknown document belongs to the corresponding category or not. We use the Reuters-21578 news data set to evaluate the performance of the proposed method.

原文English
頁面720-723
頁數4
出版狀態Published - 2001
事件10th IEEE International Conference on Fuzzy Systems - Melbourne, Australia
持續時間: 2001 12月 22001 12月 5

Other

Other10th IEEE International Conference on Fuzzy Systems
國家/地區Australia
城市Melbourne
期間01-12-0201-12-05

All Science Journal Classification (ASJC) codes

  • 軟體
  • 理論電腦科學
  • 人工智慧
  • 應用數學

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