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

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.

Publication
Proceedings of the AAAI Conference on Artificial Intelligence
Hua Xu
Hua Xu
Tenured Associate Professor, Associate Editor of Expert Systems with Application, Ph.D Supervisor