A Text Sentiment Classification Method Based on LSTM-CNN

Guangxing Wang; SeongYoon Shin; Lee， Won Joo

Journal of The Korea Society of Computer and Information

Abbr : JKSCI
2019, 24(12), pp.1-7
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science

Guangxing Wang ¹, SeongYoon Shin ², Lee， Won Joo ³

¹Jiujiang University
²군산대학교
³인하공업전문대학

ABSTRACT

With the in-depth development of machine learning, the deep learning method has made great progress, especially with the Convolution Neural Network(CNN). Compared with traditional text sentiment classification methods, deep learning based CNNs have made great progress in text classification and processing of complex multi-label and multi-classification experiments. However, there are also problems with the neural network for text sentiment classification. In this paper, we propose a fusion model based on Long-Short Term Memory networks(LSTM) and CNN deep learning methods, and applied to multi-category news datasets, and achieved good results. Experiments show that the fusion model based on deep learning has greatly improved the precision and accuracy of text sentiment classification. This method will become an important way to optimize the model and improve the performance of the model.
KEYWORDS

Machine Learning, CNN, LSTM, Text Sentiment Classification Methods, Deep Learning
REFERENCES (6)

[journal] Chetan Arora / 2015 / Automated Checking of Conformance to Requirements Templates Using Natural Language Processing / IEEE Transactions on Software Engineering / Institute of Electrical and Electronics Engineers (IEEE) 41(10) : 944~968 / 10.1109/TSE.2015.2428709.

[confproc] Mohd Ibrahim / 2010 / QClass Diagram Extraction from Textual Requirements Using Natural Language Processing (NLP)Techniques / 2010 Second International Conference on Computer Research and Development : 200~204

[confproc] Sweta P. Lende / 2016 / Question answering system on education acts using NLP techniques / 2016 World Conference on Futuristic Trends in Research and Innovation for Social Welfare(Startup Conclave) : 1~6

[confproc] C. Janarish Saju / 2017 / A Survey on Efficient Extraction of Named Entities from New Domains Using Big Data Analytics / 2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM) : 170~175

[journal] Tom Young / 2018 / Recent Trends in Deep Learning Based Natural Language Processing [Review Article] / IEEE Computational Intelligence Magazine / Institute of Electrical and Electronics Engineers (IEEE) 13(3) : 55~75 / 10.1109/MCI.2018.2840738.

[web] / THUCTC: An efficient Chinese text classification toolkit / http://thuctc.thunlp.org
KCI Citation (2)

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