• Title/Summary/Keyword: 애스팩트 마이닝

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Multi-Label Classification Approach to Effective Aspect-Mining (효과적인 애스팩트 마이닝을 위한 다중 레이블 분류접근법)

  • Jong Yoon Won;Kun Chang Lee
    • Information Systems Review
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    • v.22 no.3
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    • pp.81-97
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    • 2020
  • Recent trends in sentiment analysis have been focused on applying single label classification approaches. However, when considering the fact that a review comment by one person is usually composed of several topics or aspects, it would be better to classify sentiments for those aspects respectively. This paper has two purposes. First, based on the fact that there are various aspects in one sentence, aspect mining is performed to classify the emotions by each aspect. Second, we apply the multiple label classification method to analyze two or more dependent variables (output values) at once. To prove our proposed approach's validity, online review comments about musical performances were garnered from domestic online platform, and the multi-label classification approach was applied to the dataset. Results were promising, and potentials of our proposed approach were discussed.