Abstract
In this paper, we report a short answer grading system in Chinese. We build a system based on standard machine learning approaches and test it with translated corpus from two publicly available corpus in English. The experiment results show similar results on two different corpus as in English.- Anthology ID:
- W18-3718
- Volume:
- Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Yuen-Hsien Tseng, Hsin-Hsi Chen, Vincent Ng, Mamoru Komachi
- Venue:
- NLP-TEA
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 125–129
- Language:
- URL:
- https://aclanthology.org/W18-3718
- DOI:
- 10.18653/v1/W18-3718
- Cite (ACL):
- Shih-Hung Wu and Wen-Feng Shih. 2018. A Short Answer Grading System in Chinese by Support Vector Approach. In Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications, pages 125–129, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- A Short Answer Grading System in Chinese by Support Vector Approach (Wu & Shih, NLP-TEA 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W18-3718.pdf