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Sentiment Classification of Russian Texts Using Automatically Generated Thesaurus

机译:使用自动生成的词库对俄语文本进行情感分类

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This paper is devoted to an approach for sentiment classification of Russian texts applying an automatic thesaurus of the subject area. This approach consists of a standard machine learning classifier and a procedure embedded into it, that uses thesaurus relationships for better sentiment analysis. The thesaurus is generated fully automatically and does not require expert's involvement into classification process. Experiments conducted with the approach and four Russian-language text corpora, show effectiveness of thesaurus application to sentiment classification.
机译:本文致力于运用主题领域的自动词库对俄语文本进行情感分类的方法。这种方法由标准的机器学习分类器和嵌入其中的过程组成,该分类器使用同义词库关系进行更好的情感分析。同义词库是完全自动生成的,不需要专家参与分类过程。使用该方法和四个俄语文本语料库进行的实验表明,同义词库在情感分类中的应用效果。

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