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 |
|---|---|
| Title of host publication | IEEE International Conference on Fuzzy Systems |
| Pages | 720-723 |
| Number of pages | 4 |
| Volume | 2 |
| Publication status | Published - 2001 |
| 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 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Software
- Artificial Intelligence
- Applied Mathematics
Cite this
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Hierarchical fuzzy-KNN networks for news documents categorization. / Chiang, Jung-Hsien; Chen, Yan Cheng.
IEEE International Conference on Fuzzy Systems. Vol. 2 2001. p. 720-723.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Hierarchical fuzzy-KNN networks for news documents categorization
AU - Chiang, Jung-Hsien
AU - Chen, Yan Cheng
PY - 2001
Y1 - 2001
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0036343391&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0036343391&partnerID=8YFLogxK
M3 - Conference contribution
VL - 2
SP - 720
EP - 723
BT - IEEE International Conference on Fuzzy Systems
ER -