2020
AAAI
AAAI 2020
SATNet: Symmetric Adversarial Transfer Network Based on Two-Level Alignment Strategy towards Cross-Domain Sentiment Classification (Student Abstract)
Abstract
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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Interdisciplinary Bridge
- Artificial Intelligence and Natural Language Processing
Topics
Machine Learning > Learning Types > Adversarial Learning
Machine Learning > Application Areas > Domain Adaptation
Machine Learning > Learning Types > Transfer Learning
Natural Language Processing > Applications > Sentiment Analysis
Deep Learning > Learning Types > Adversarial Learning
Deep Learning > Learning Types > Transfer Learning
Deep Learning > Learning Types > Domain Adaptation