Transformer-based Multi-Aspect Modeling for Multi-Aspect Multi-Sentiment Analysis. Zhen Wu, Chengcan Ying, Xinyu Dai, Shujian Huang, Jiajun Chen. NLPCC 2020.
- pytorch=1.7.1
- python=3.7
Download the pretrained RoBERTa model (link, password:2fv2
) and unzip it into the folder pretrained
.
The MAMS data is preprocessed by the script preprocess.py
. The original and preprocessed versions of the data are provided in the folder data
.
Run the command python main_ATSA.py
to train and test the ATSA model.
You can change training settings in the file configs.py
.
Run the command python main_ACSA.py
to train and test the ACSA model.
You can change training settings in the file configs.py
.
If you use the code, please cite our paper:
@InProceedings{10.1007/978-3-030-60457-8_45,
author="Wu, Zhen
and Ying, Chengcan
and Dai, Xinyu
and Huang, Shujian
and Chen, Jiajun",
editor="Zhu, Xiaodan
and Zhang, Min
and Hong, Yu
and He, Ruifang",
title="Transformer-Based Multi-aspect Modeling for Multi-aspect Multi-sentiment Analysis",
booktitle="Natural Language Processing and Chinese Computing",
year="2020",
publisher="Springer International Publishing",
address="Cham",
pages="546--557",
isbn="978-3-030-60457-8"
}
[1]. Zhen Wu, Chengcan Ying, Xinyu Dai, Shujian Huang, Jiajun Chen. Transformer-based Multi-Aspect Modeling for Multi-Aspect Multi-Sentiment Analysis. NLPCC 2020.
[2]. Qingnan Jiang, Lei Chen, Ruifeng Xu, Xiang Ao, Min Yang. A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis. EMNLP-IJCNLP 2019.