作者
Feng Yu, Huabin Wang, Dequan Zheng, Geli Fei
发表日期
2010/10/23
研讨会论文
2010 International Conference on Artificial Intelligence and Computational Intelligence
卷号
1
页码范围
418-422
出版商
IEEE
简介
The major goal in transfer learning is that the knowledge learned in one environment will help new tasks in another or changing environment. In this paper, a novel transfer learning approach is presented and the transfer knowledge will be applied to text categorization. First, we will learn the transfer knowledge from different category data respectively, and then, different classifiers will be constructed, final, transfer knowledge will guide other categorization task. We compared with SVM, K-NN and Centroid methods. Experiments showed that transfer learning method was effective and got a better performance in text categorization, it can help new tasks in another new environment or changing environment.
学术搜索中的文章
F Yu, H Wang, D Zheng, G Fei - 2010 International Conference on Artificial Intelligence …, 2010