Employing Auto-Annotated Data for Government Document Classification

Author:

Song Yajun1,Li Zeyuan1,He Jie1,Li Zesong1,Fang Xin1,Chen Dagang1

Affiliation:

1. CETC Big Data Research Institute Co., Ltd., Guiyang, China

Publisher

ACM Press

Reference19 articles.

1. Zeyuan Li, Jie He, Dagang Chen, Xin Fang, Yajun Song, and Zesong Li. 2018. A Hybrid Approach for Measuring Similarity between Government Documents of China. In Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence (CSAI '18). ACM, New York, NY, USA, 431--435.

2. Sebastiani F. Machine learning in automated text categorization. ACM Computing Surveys, 2002, 34(1):1--47.

3. Nargesian, F.; Samulowitz, H.; Khurana, U.; Khalil, E. B.; and Turaga, D. 2017. Learning feature engineering for classification. In IJCAI, 2529--2535.

4. Cover, T. M., and Thomas, J. A. 2012. Elements of information theory. John Wiley & Sons.

5. Ng, A. Y. 2004. Feature selection, L1 vs. L2 regularization, and rotational invariance. In ICML, 78.

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