Sentiment Classification of Chinese Contrast Sentences
نویسندگان
چکیده
We present the study of sentiment classification of Chinese contrast sentences in this paper, which are one of the commonly used language constructs in text. In a typical review, there are at least around 6% of such sentences. Due to the complex contrast phenomenon, it is hard to use the traditional bag-of-words to model such sentences. In this paper, we propose a Two-Layer Logistic Regression (TLLR) model to leverage such relationship in sentiment classification. According to different connectives, our model can treat different clauses differently in sentiment classification. Experimental results show that TLLR model can effectively improve the performance of sentiment classification of Chinese contrast sentences.
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