论文阅读笔记：DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
摘要： 本文通过提出Dual crOss-sharEd RNN framework (DOER)模型来在同时解决属性级实体抽取及情感分类任务，这一模型采用两个RNN分别处理两个任务，并采用一个cross-shared 单元将两部分的隐藏层表示进行互相增强。并采用两个辅助任务：实体长度预测和输入单词情感极性预测作为辅助任务与模型进行联合训练，实验结果在三个数据集上有SOTA的表现。 1.简介： 本文
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