Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022)

Big Data Based Transfer Learning for Sentiment Classification with Multiple Source Domains

Authors
Qing Li1, Gang Wang1, *, Guowu Yang1
1School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
*Corresponding author. Email: carbite_wg@163.com
Corresponding Author
Gang Wang
Available Online 23 December 2022.
DOI
10.2991/978-94-6463-034-3_26How to use a DOI?
Keywords
Big Data; Transfer Learning; Sentiment Classification
Abstract

Sentiment classification, served as a curial technology in natural language processing and computational linguistics, has drawn a lot of attentions from researchers. However, due to the high cost of manual labeling in the era of big data, conventional methods of sentiment classification are unqualified to be employed in a new domain directly. Hence, in this paper, we explore big data based transfer learning for sentiment classification with multiple source domains. To solve the problem of inherent domain gap, we propose a novel framework Adversarial cross-domain sentiment classification with weighted domain-dependent fEAture learning dubbed AdEA. Specifically, AdEA involves an individual domain-invariant feature extractor and several domain-dependent feature extractors. To obtain the domain-invariant feature, we use a reversed discriminator loss for these extractors. Furthermore, we propose a weighted learning module to reinforce the relationship of domain-dependent features between source and target domains. Integrated with these two domain-related features, AdEA is able to achieve better capability of cross-domain sentiment classification. Experimental results show the effectiveness of our proposed method.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
23 December 2022
ISBN
978-94-6463-034-3
ISSN
2589-4900
DOI
10.2991/978-94-6463-034-3_26How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Qing Li
AU  - Gang Wang
AU  - Guowu Yang
PY  - 2022
DA  - 2022/12/23
TI  - Big Data Based Transfer Learning for Sentiment Classification with Multiple Source Domains
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022)
PB  - Atlantis Press
SP  - 256
EP  - 265
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-034-3_26
DO  - 10.2991/978-94-6463-034-3_26
ID  - Li2022
ER  -