SATNet: Symmetric Adversarial Transfer Network Based on Two-Level Alignment Strategy towards Cross-Domain Sentiment Classification (Student Abstract)

Authors

  • Yu Cao Tsinghua University
  • Hua Xu Tsinghua University

DOI:

https://doi.org/10.1609/aaai.v34i10.7153

Abstract

In recent years, domain adaptation tasks have attracted much attention, especially, the task of cross-domain sentiment classification (CDSC). In this paper, we propose a novel domain adaptation method called Symmetric Adversarial Transfer Network (SATNet). Experiments on the Amazon reviews dataset demonstrate the effectiveness of SATNet.

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Published

2020-04-03

How to Cite

Cao, Y., & Xu, H. (2020). SATNet: Symmetric Adversarial Transfer Network Based on Two-Level Alignment Strategy towards Cross-Domain Sentiment Classification (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 34(10), 13763-13764. https://doi.org/10.1609/aaai.v34i10.7153

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Section

Student Abstract Track