Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction

Yidong Wang, Hao Wu, Ao Liu, Wenxin Hou, Zhen Wu, Jindong Wang, Takahiro Shinozaki, Manabu Okumura, Yue Zhang


Abstract
Target-oriented Opinion Words Extraction (TOWE) is a fine-grained sentiment analysis task that aims to extract the corresponding opinion words of a given opinion target from the sentence. Recently, deep learning approaches have made remarkable progress on this task. Nevertheless, the TOWE task still suffers from the scarcity of training data due to the expensive data annotation process. Limited labeled data increase the risk of distribution shift between test data and training data. In this paper, we propose exploiting massive unlabeled data to reduce the risk by increasing the exposure of the model to varying distribution shifts. Specifically, we propose a novel Multi-Grained Consistency Regularization (MGCR) method to make use of unlabeled data and design two filters specifically for TOWE to filter noisy data at different granularity. Extensive experimental results on four TOWE benchmark datasets indicate the superiority of MGCR compared with current state-of-the-art methods. The in-depth analysis also demonstrates the effectiveness of the different-granularity filters.
Anthology ID:
2022.coling-1.617
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
7075–7085
Language:
URL:
https://aclanthology.org/2022.coling-1.617
DOI:
Bibkey:
Cite (ACL):
Yidong Wang, Hao Wu, Ao Liu, Wenxin Hou, Zhen Wu, Jindong Wang, Takahiro Shinozaki, Manabu Okumura, and Yue Zhang. 2022. Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction. In Proceedings of the 29th International Conference on Computational Linguistics, pages 7075–7085, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction (Wang et al., COLING 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.coling-1.617.pdf
Code
 towessl/towessl