Applying Sentiment-oriented Sentence Filtering to Multilingual Review Classification
Applying Sentiment-oriented Sentence Filtering to Multilingual Review Classification
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发表时间：
2011-11
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通讯作者：
Takashi Inui;Mikio Yamamoto
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作者：
Takashi Inui;Mikio Yamamoto
A method for multilingual review classification is described. In this classification task, machine translation techniques are used to remove language gaps in the dataset, but many translation errors occur as a side-effect. These errors cause a decrease in the review classification performance. To resolve this problem, we introduce a sentiment-oriented sentence filtering module to the process of multilingual review classification. Experimental results showed that the proposed method achieved 81.7% classification accuracy for the evaluation data.
