Text Sentiment Classification Based on GDBN Neural Network

doi:10.15888/j.cnki.csa.006723

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Home > Archive>Volume 28, Issue 1, 2019 >163-168. DOI:10.15888/j.cnki.csa.006723

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Text Sentiment Classification Based on GDBN Neural Network
DOI:
                        10.15888/j.cnki.csa.006723
                    
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                        CHEN Ying-XiCHEN Ying-Xi
College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China
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LIAO Xiao-DongLIAO Xiao-Dong
College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China;Key Laboratory of Optoelectronic Science and Technology for Medicine(Ministry of Education) Cum. Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou 350007, China;Fujian Provincial Engineering Research Center for Optoelectronic Sensors and Intelligent Information, Fuzhou 350007, China
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SU Li-YueSU Li-Yue
College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China
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TAO ZhuangTAO Zhuang
College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China
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Abstract:

Text sentiment classification is a hot topic in the field of natural language processing. One of its important applications is to dig out important information from online comments and grasp the trend of public opinion on the Internet. Therefore, this study proposes a method of text sentiment classification based on GDBN neural network. The algorithm improves the hidden layer in the DBN neural network by introducing genetic algorithm, which is of powerful global searching ability, and the algorithm optimizes the number of hidden units and obtains the appropriate value of the current model, then the modeling and feature extraction of this model. Finally, we can classify the extracted features of the BP neural network. By testing multiple data, the results show that the proposed algorithm is effective.

Key words:text sentiment classification;optimization search;genetic algorithm;deep belief networks

Reference

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陈颖熙,廖晓东,苏例月,陶状.基于GDBN网络的文本情感倾向分类算法.计算机系统应用,2019,28(1):163-168

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Received:July 02,2018
Revised:July 27,2018
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Online: December 27,2018
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