論文閱讀筆記：Transformation Networks for Target-Oriented Sentiment Classification
原文鏈接 本文是香港中文大學和騰訊AI實驗室2018年在ACL上發表的論文 摘要 本文模型爲三層結構，最下面一層爲雙向LSTM，最上一層爲CNN，替代基於注意機制的RNN 去提取最重要的分類特徵，由於 CNN 很難捕捉目標實體信息，所以本文提出了一個特徵變換組件來將實體信息引入到單詞的語義表示當中。但這個特徵變換過程可能會使上下文信息丟失。所以本文又提出了一種「上下文保留」機制，可將帶有上下文
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