Abstract
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.
| Original language | English |
|---|---|
| Pages | 720-723 |
| Number of pages | 4 |
| Publication status | Published - 2001 Dec 1 |
| Event | 10th IEEE International Conference on Fuzzy Systems - Melbourne, Australia Duration: 2001 Dec 2 → 2001 Dec 5 |
Other
| Other | 10th IEEE International Conference on Fuzzy Systems |
|---|---|
| Country | Australia |
| City | Melbourne |
| Period | 01-12-02 → 01-12-05 |
All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Artificial Intelligence
- Applied Mathematics
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Cite this
Chiang, J-H., & Chen, Y. C. (2001). Hierarchical fuzzy-KNN networks for news documents categorization. 720-723. Paper presented at 10th IEEE International Conference on Fuzzy Systems, Melbourne, Australia.