论文阅读笔记：Transformation Networks for Target-Oriented Sentiment Classification
原文链接 本文是香港中文大学和腾讯AI实验室2018年在ACL上发表的论文 摘要 本文模型为三层结构，最下面一层为双向LSTM，最上一层为CNN，替代基于注意机制的RNN 去提取最重要的分类特征，由于 CNN 很难捕捉目标实体信息，所以本文提出了一个特征变换组件来将实体信息引入到单词的语义表示当中。但这个特征变换过程可能会使上下文信息丢失。所以本文又提出了一种“上下文保留”机制，可将带有上下文
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