NDLI: A Text Sentiment Classification Modeling Method Based on Coordinated CNN-LSTM-Attention Model

Content Provider	IET Digital Library
Author	Zhang, Yangsen Zheng, Jia Jiang, Yuru Huang, Gaijuan Chen, Ruoyu
Abstract	The major challenge that text sentiment classification modeling faces is how to capture the intrinsic semantic, emotional dependence information and the key part of the emotional expression of text. To solve this problem, we proposed a Coordinated CNN-LSTM-Attention(CCLA) model. We learned the vector representations of sentence with CCLA unit. Semantic and emotional information of sentences and their relations are adaptively encoded to vector representations of document. We used softmax regression classifier to identify the sentiment tendencies in the text. Compared with other methods, the CCLA model can well capture the local and long distance semantic and emotional information. Experimental results demonstrated the effectiveness of CCLA model. It shows superior performances over several state-of-the-art baseline methods.
Starting Page	120
Ending Page	126
Page Count	7
ISSN	10224653
Volume Number	28
e-ISSN	20755597
Issue Number	Issue 1, Jan (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/cje/28/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/cje.2018.11.004
Journal	Chinese Journal of Electronics
Publisher Date	2019-01-01
Access Restriction	Open
Rights Holder	© Chinese Institute of Electronics
Subject Keyword	CCLA Model CCLA Unit Computer Vision And Image Processing Technique Coordinated CNN-LSTM-Attention Model Document Processing Technique Emotion Recognition Emotional Dependence Information Emotional Expression Image Classification Intrinsic Semantic Dependence Information Key Part Knowledge Engineering Technique Learning in AI Pattern Classification Regression Analysis Sentiment Tendencies State-of-the-art Baseline Method Statistics Text Analysis Text Sentiment Classification Modeling Method
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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