Adversarial Training Based Multi-Source Unsupervised Domain Adaptation for Sentiment Analysis

10 Jun 2020Yong DaiJian LiuXiancong RenZenglin Xu

Multi-source unsupervised domain adaptation (MS-UDA) for sentiment analysis (SA) aims to leverage useful information in multiple source domains to help do SA in an unlabeled target domain that has no supervised information. Existing algorithms of MS-UDA either only exploit the shared features, i.e., the domain-invariant information, or based on some weak assumption in NLP, e.g., smoothness assumption... (read more)

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