@inproceedings{7dcaccb73d5141c597e316bbc32d4fa0,
title = "History question classification and representation for Chinese Gaokao",
abstract = "In this paper, we propose a question representation based on entity labeling and question classification for a automatic question answering system of Chinese Gaokao history question. A CRF model is used for the entity labeling and SVM/ CNN/LSTM models are tested for question classification. Our experiments show that CRF model provides a high performance when used to label informative entities out while neural networks has a promising performance for the question classification task. With both entity labeling and question classification models of high performance, we can provide the KB-based question answering system with a question representation of high reliability. Then the question answering system can do more good work depending on the key information our models provide.",
keywords = "CNN, CRF, LSTM, NER, Question Classification",
author = "Ke Yu and Qiuzhi Liu and Yuqing Zheng and Tiejun Zhao and Dequan Zheng",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 20th International Conference on Asian Language Processing, IALP 2016 ; Conference date: 21-11-2016 Through 23-11-2016",
year = "2017",
month = mar,
day = "10",
doi = "10.1109/IALP.2016.7875951",
language = "英语",
series = "Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "129--132",
editor = "Minghui Dong and Chung-Hsien Wu and Yanfeng Lu and Haizhou Li and Yuen-Hsien Tseng and Liang-Chih Yu and Lung-Hao Lee",
booktitle = "Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016",
address = "美国",
}