| Issue |
MATEC Web Conf.
Volume 336, 2021
2020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
|
|
|---|---|---|
| Article Number | 06017 | |
| Number of page(s) | 7 | |
| Section | Artificial Recognition and Application | |
| DOI | https://doi.org/10.1051/matecconf/202133606017 | |
| Published online | 15 February 2021 | |
Tibetan interrogative sentence recognition and classification based on phrase features
1 College of Computer Science and Technology, Qinghai Normal University, Qinghai Xining 810016, China
2 School of Computer Science and Technology, Southwest Minzu University, Sichuan Chengdu 610041, China
3 Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province, Qinghai Xining 810008, China
4 Key Laboratory of Tibetan Information Processing, Ministry of Education, Qinghai Xining 810008, China
* Corresponding author: 1402554093@qq.com
The recognition of Tibetan interrogative sentences is a basic work in natural language processing, which has a wide application value in terms of Tibetan syntactic analysis, semantic analysis, intelligent question answering, search engine and other research fields. Employing interrogative pronouns as a entry point to analyze the phrase features before and after interrogative pronouns, the paper proposes a method for Tibetan interrogative sentence recognition and classification based on phrase features by designing a Tibetan interrogative sentence recognition and classification model based on phrase features. Experimental results show that the recognition accuracy, recall rate and F value of this method are 98.21%, 100.00% and 99.10% respectively, and the average classification accuracy, recall rate and F value are 96.98%, 100.00% and 98.39%, respectively.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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