Research on customer opinion summarization using topic mining and deep neural network-Reference-Cited by-同舟云学术

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Research on customer opinion summarization using topic mining and deep neural network

Published:2021-07 Issue: Volume:185 Page:88-114
ISSN:0378-4754
Container-title:Mathematics and Computers in Simulation
language:en
Short-container-title:Mathematics and Computers in Simulation

Author:

Hong Ming,Wang Heyong

Funder

National Nature Science Foundation of China

Fundamental Research Funds for Guangdong Natural Science Foundation

Guangdong soft Science Foundation

Guangdong Philosophy and Social Science

Science and Technology Development Minister of Education

Publisher

Elsevier BV

Subject

Applied Mathematics,Modelling and Simulation,Numerical Analysis,General Computer Science,Theoretical Computer Science

Reference89 articles.

1. M. Abdullah, M. Hadzikadic, S. Shaikh, SEDAT: Sentiment and emotion detection in Arabic Text using CNN-LSTM deep learning, in: Proceedings of 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), Orlando, FL, Dec. 17-20 2018, 2018.

2. F. Akba, I.T. Medeni, M.S. Guzel, et al. Assessment of iterative semi-supervised feature selection learning for sentiment analyses: digital currency markets, in: Proceedings of 14th IEEE International Conference on Semantic Computing, San Diego, CA, Feb 03-05 2020.

3. How intense are you? predicting intensities of emotions and sentiments using stacked ensemble [application notes];Akhtar;IEEE Comput. Intell. Mag.,2020

4. Fuzzy ontology and LSTM-based text mining: A transportation network monitoring system for assisting travel;Ali;Sensors,2019

5. Latent Dirichlet allocation (LDA) for topic modeling of the CFPB consumer complaints;Bastani;Expert Syst. Appl.,2019

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