Applying Sentiment-oriented Sentence Filtering to Multilingual Review Classification
نویسندگان
چکیده
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.
منابع مشابه
Multilingual Sentiment and Subjectivity Analysis
Subjectivity and sentiment analysis focuses on the automatic identification of private states, such as opinions, emotions, sentiments, evaluations, beliefs, and speculations in natural language. While subjectivity classification labels text as either subjective or objective, sentiment classification adds an additional level of granularity, by further classifying subjective text as either positi...
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