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

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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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  -