A Dynamic Centroid Text Classification Approach by Learning from Unlabeled Data
文献类型：会议论文
| 作者 | Jiang, Cuicui; Zhu, Dingju; Jiang, Qingshan |
| 出版日期 | 2013 |
| 会议名称 | 3rd International Conference on Multimedia Technology (ICMT) |
| 会议地点 | Guangzhou, PEOPLES R CHINA |
| 英文摘要 | The centroid-based classification has proved to be a simple and yet efficient method for text classification. However, the performance of centroid-based classifier depends heavily on the quantity of labeled training set. It is easy and cheap to collect enormous unlabeled data from digital resources, while it is difficult and costly to label these data for training classifiers. To address this problem, we propose a dynamic centroid text classification approach which learns from unlabeled texts to construct dynamic centroids. The main idea of the approach is to take the unlabeled texts with high classifying confidence into consideration to adjust the centroids dynamically. Experiments on two public corpora have indicated the effectiveness of our text classification approach in the case of spare labeled training set. |
| 收录类别 | ISTP |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/5130]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | 2013 |
| 推荐引用方式 GB/T 7714 | Jiang, Cuicui,Zhu, Dingju,Jiang, Qingshan. A Dynamic Centroid Text Classification Approach by Learning from Unlabeled Data[C]. 见:3rd International Conference on Multimedia Technology (ICMT). Guangzhou, PEOPLES R CHINA. |
入库方式： OAI收割
来源：深圳先进技术研究院
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