Aspect Embedding on Memory Network for Aspect Sentiment Classification [基于词嵌入与记忆网络的方面情感分类]

作者：Liu Y.; Zhang J.^*; Yu Z.; Liu Y.; Cheng X.

来源：Pattem Recognition and Aitificial Intelligence, 2019, 32(12): 1093-1099.

DOI：10.16451/j.cnki.issn1003-6059.201912004

• Aspect Embedding
• Aspect Sentiment Classification
• Attention Mechanism
• Memory Neural Network

A comment contains multiple aspects and sentiments, and therefore it is difficult to classify sentiment polarity of different aspects correctly. A model combining aspect embedding with memory neural network is proposed to identify the sentiment of aspects in a comment. The aspect word vector is introduced into different modules of the memory network. The semantic information of the word is reinforced. The attention mechanism is guided to capture the relevant context, and thus the sentiment classification effect in the aspect is improved. Experimental results on short text English comments of SemEval 2014 Task 4 dataset and the long-text Chinese news dataset indicate that the proposed method achieves good classification effect and fully verifies the validity of the word embedding information introduced into the framework of the memory network.

• 单位
  中国科学院大学