Open AccessA Key Sentences Based Convolution Neural Network for Text Sentiment Classification
Author(s) -
Mohan Zhang,
Yang Xiang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1229/1/012062
Subject(s) - computer science , key (lock) , artificial intelligence , convolutional neural network , natural language processing , sentiment analysis , representation (politics) , process (computing) , artificial neural network , convolution (computer science) , speech recognition , computer security , politics , political science , law , operating system
Existing research treated all sentences in the text on an equal basis during the training process and did not consider that key sentences tend to have a stronger influence. We propose a Convolutional Neural Network text sentiment classification model based on the key sentences enhancement. The proposed model can identify key sentences in the text and generate text representation based on these key sentences to reduce noise and improve the accuracy of the model sentiment classification. The experiment results show that the proposed model improves the accuracy of the text sentiment classification compared with other classic text sentiment classification models.