Cross-Domain Sentiment Classification by Capsule Network With Semantic Rules
نویسندگان
چکیده
منابع مشابه
Active Learning for Cross-domain Sentiment Classification
In the literature, various approaches have been proposed to address the domain adaptation problem in sentiment classification (also called cross-domain sentiment classification). However, the adaptation performance normally much suffers when the data distributions in the source and target domains differ significantly. In this paper, we suggest to perform active learning for cross-domain sentime...
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Sentiment analysis has been studied for decades, and it is widely used in many real applications such as media monitoring. In sentiment analysis, when addressing the problem of limited labeled data from the target domain, transfer learning, or domain adaptation, has been successfully applied, which borrows information from a relevant source domain with abundant labeled data to improve the predi...
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Sentiment analysis aims to determine the attitude and the feelings of the opinion holder for the given reviews. Reviews contain features and opinion. Automatic extraction of customer opinion which is used by both manufacturers and customers. The Sentiment Classifier might classify reviews as positive or negative based on the sentiment expressed in review. Sentiment classification is domain depe...
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In this paper, we focus on the tasks of cross-domain sentiment classification. We find across different domains, features with some types of part-of-speech (POS) tags are domain-dependent, while some others are domain-free. Based on this finding, we proposed a POS-based ensemble model to efficiently integrate features with different types of POS tags to improve the classification performance. W...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2018
ISSN: 2169-3536
DOI: 10.1109/access.2018.2874623