| Automatic text classification based on rough set and improved quick-reduce algorithm | |
| Jiang, MH ; Deng, BX ; Sheng, XW ; Tang, XF ; Ruan, QQ ; Yuan, BZ | |
| 2010-05-10 ; 2010-05-10 | |
| 会议名称 | 2004 7TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS 1-3 ; 7th International Conference on Signal Processing ; Beijing, PEOPLES R CHINA ; Web of Science |
| 关键词 | automatic classification rough set decision table reduction algorithm Computer Science, Artificial Intelligence Engineering, Electrical & Electronic Imaging Science & Photographic Technology Telecommunications |
| 中文摘要 | This paper proposes a fast dimensionality reduction algorithm for automatic text classifications (TC). which introduces Rough Set theory that can greatly reduce the document vector dimensions by the reduction algorithm. The experimental results prove that the proposed algorithm is very successful, it can not only keep important low-frequency words but also remove high-frequency words with no use in classification. Thus our algorithm reduces effectively the dimensional space, and reaches higher accuracy while losing less useful information compared with the conventional reduction methods. |
| 会议录出版者 | PUBLISHING HOUSE ELECTRONICS INDUSTRY ; BEIJING ; PO BOX 173 WANSHOU ROAD, BEIJING 100036, PEOPLES R CHINA |
| 语种 | 英语 ; 英语 |
| 内容类型 | 会议论文 |
| 源URL | [http://hdl.handle.net/123456789/19925]  |
| 专题 | 清华大学 |
| 推荐引用方式 GB/T 7714 | Jiang, MH,Deng, BX,Sheng, XW,et al. Automatic text classification based on rough set and improved quick-reduce algorithm[C]. 见:2004 7TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS 1-3, 7th International Conference on Signal Processing, Beijing, PEOPLES R CHINA, Web of Science. |
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