Attention-Based LSTM for Target-Dependent Sentiment Classification

被引：0

作者：

Yang, Min ^{[1
]}

Tu, Wenting ^{[1
]}

Wang, Jingxuan ^{[1
]}

Xu, Fei ^{[2
]}

Chen, Xiaojun ^{[3
]}

机构：

[1] Univ Hong Kong, Hong Kong, Peoples R China

[2] Chinese Acad Sci, Beijing, Peoples R China

[3] Shenzhen Univ, Shenzhen, Peoples R China

来源：

THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2017年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：5013 / 5014

页数：2

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