Attention Based LSTM for Target Dependent Sentiment Classification
Proceedings of the AAAI Conference on Artificial IntelligencePublished 12 February 2017Open access
Min Yang, Wenting Tu, Jingxuan Wang, Fei Xu, Xiaojun Chen
Citations209
SJR score0.13
SNIP0.00
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TL;DR
An attention-based bidirectional LSTM approach to improve the target-dependent sentiment classification by learning the alignment between the target entities and the most distinguishing features.
Abstract
We present an attention-based bidirectional LSTM approach to improve the target-dependent sentiment classification. Our method learns the alignment between the target entities and the most distinguishing features. We conduct extensive experiments on a real-life dataset. The experimental results show that our model achieves state-of-the-art results.
Keywords
Computer Science
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