JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2017, Vol. 52 ›› Issue (9): 19-25.doi: 10.6040/j.issn.1671-9352.1.2016.PC4

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An emotional classification method based on joint deep learning model

YANG Yan, XU Bing*, YANG Mu-yun, ZHAO Jing-jing   

  1. Harbin Institute of Technology, School of Computer Science and Technology, Harbin 150000, Heilongjiang, China
  • Received:2016-11-25 Online:2017-09-20 Published:2017-09-15

Abstract: According to the analysis of emotional problems in the modeling of long and short sentences different characteristics to sentiment classification, this paper proposes a classification algorithm based on the model of joint deep learning. Fusion of long short term memory model of the method(LSTM)and convolutional neural network(CNN)on film reviews emotional polarity discrimination, in the method, LSTM model was used to model context, through the word iteration to get feature vector context, and CNN model was used to automatically discover features from the word vector sequence, and integrating local features from the local feature extraction into global features to improve the classification results. The method proposed in this paper is to obtain the best results of the system accuracy in the task of the COAE2016 evaluation task 2.

Key words: sentiment classification, CNN, LSTM

CLC Number: 

  • TP391.1
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