这篇博客总结了Tang等人2016年的论文，介绍了如何使用深度记忆网络进行方面级情感分类。该模型利用注意力机制和多跳计算层，能更好地捕捉上下文信息并强调每个词的重要性。尽管LSTM等传统模型有其优势，但无法显式展示关键上下文线索。论文在笔记本电脑和餐厅数据集上进行了实验，并分享了模型训练和参数共享的细节。
Aspect Level Sentiment Classification with Deep Memory Network
论文来源：Tang, D., Qin, B., & Liu, T. (2016). Aspect level sentiment classification with deep memory network. arXiv preprint arXiv:1605.08900.
原文链接：http://blog.youkuaiyun.com/rxt2012kc/article/details/73770408
advantages
Neural models are of growing interest for their capacity to learn text representation from data without careful engineering of features, and to capture semantic relations between aspect and context words in a more scalable way than feature based SVM.
disadvantage
Despite these advantages, conventional neu
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