Multi-grained Attention Network for Aspect-Level Sentiment Classification

Feifan Fan, Yansong Feng, Dongyan Zhao


Abstract
We propose a novel multi-grained attention network (MGAN) model for aspect level sentiment classification. Existing approaches mostly adopt coarse-grained attention mechanism, which may bring information loss if the aspect has multiple words or larger context. We propose a fine-grained attention mechanism, which can capture the word-level interaction between aspect and context. And then we leverage the fine-grained and coarse-grained attention mechanisms to compose the MGAN framework. Moreover, unlike previous works which train each aspect with its context separately, we design an aspect alignment loss to depict the aspect-level interactions among the aspects that have the same context. We evaluate the proposed approach on three datasets: laptop and restaurant are from SemEval 2014, and the last one is a twitter dataset. Experimental results show that the multi-grained attention network consistently outperforms the state-of-the-art methods on all three datasets. We also conduct experiments to evaluate the effectiveness of aspect alignment loss, which indicates the aspect-level interactions can bring extra useful information and further improve the performance.
Anthology ID:
D18-1380
Volume:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Month:
October-November
Year:
2018
Address:
Brussels, Belgium
Editors:
Ellen Riloff, David Chiang, Julia Hockenmaier, Jun’ichi Tsujii
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
3433–3442
Language:
URL:
https://aclanthology.org/D18-1380
DOI:
10.18653/v1/D18-1380
Bibkey:
Cite (ACL):
Feifan Fan, Yansong Feng, and Dongyan Zhao. 2018. Multi-grained Attention Network for Aspect-Level Sentiment Classification. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 3433–3442, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Multi-grained Attention Network for Aspect-Level Sentiment Classification (Fan et al., EMNLP 2018)
Copy Citation:
PDF:
https://aclanthology.org/D18-1380.pdf
Data
SemEval-2014 Task-4