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• W2167660864 abstract "The lack of Chinese sentiment corpora limits the research progress on Chinese sentiment classification. However, there are many freely available English sentiment corpora on the Web. This paper focuses on the problem of cross-lingual sentiment classification, which leverages an available English corpus for Chinese sentiment classification by using the English corpus as training data. Machine translation services are used for eliminating the language gap between the training set and test set, and English features and Chinese features are considered as two independent views of the classification problem. We propose a cotraining approach to making use of unlabeled Chinese data. Experimental results show the effectiveness of the proposed approach, which can outperform the standard inductive classifiers and the transductive classifiers." @default.
• W2167660864 created "2016-06-24" @default.
• W2167660864 creator A5029568096 @default.
• W2167660864 date "2009-01-01" @default.
• W2167660864 modified "2023-10-12" @default.
• W2167660864 title "Co-training for cross-lingual sentiment classification" @default.
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• W2167660864 doi "https://doi.org/10.3115/1687878.1687913" @default.
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