基于时间注意力胶囊网络的维吾尔语情感分类模型(Uyghur Sentiment Classification Model Based on Temporal Attention Capsule Networks)
Hantian Luo (罗涵天), Yating Yang (杨雅婷), Rui Dong (董瑞), Bo Ma (马博)
Abstract
维吾尔语属于稀缺资源语言,如何在资源有限的情况下提升维吾尔语情感分类模型的性能,是目前待解决的问题。本文针对现有维吾尔语情感分析因为泛化能力不足所导致的分类效果不佳的问题,提出了基于时间卷积注意力胶囊网络的维吾尔语情感分类模型匨協十匭千卡印匩。本文在维吾尔语情感分类数据集中进行了实验并且从多个评价指标(准确率,精确率,召回率,F1值)进行评估,实验结果表明本文提出的模型相比传统深度学习模型可以有效提升维吾尔语情感分类的各项指标。- Anthology ID:
- 2021.ccl-1.24
- Volume:
- Proceedings of the 20th Chinese National Conference on Computational Linguistics
- Month:
- August
- Year:
- 2021
- Address:
- Huhhot, China
- Venue:
- CCL
- SIG:
- Publisher:
- Chinese Information Processing Society of China
- Note:
- Pages:
- 248–257
- Language:
- Chinese
- URL:
- https://aclanthology.org/2021.ccl-1.24
- DOI:
- Cite (ACL):
- Hantian Luo, Yating Yang, Rui Dong, and Bo Ma. 2021. 基于时间注意力胶囊网络的维吾尔语情感分类模型(Uyghur Sentiment Classification Model Based on Temporal Attention Capsule Networks). In Proceedings of the 20th Chinese National Conference on Computational Linguistics, pages 248–257, Huhhot, China. Chinese Information Processing Society of China.
- Cite (Informal):
- 基于时间注意力胶囊网络的维吾尔语情感分类模型(Uyghur Sentiment Classification Model Based on Temporal Attention Capsule Networks) (Luo et al., CCL 2021)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.ccl-1.24.pdf