International Journal of Advanced Culture Technology

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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A Study on Korean Sentiment Analysis Rate Using Neural Network and Ensemble Combination

  • Sim, YuJeong (Graduate School of Smart Convergence Kwangwoon University) ;
  • Moon, Seok-Jae (Institute of Information Technology, KwangWoon University) ;
  • Lee, Jong-Youg (Ingenium College of Liberal Arts, KwangWoon University)
  • Received : 2021.08.11
  • Accepted : 2021.12.02
  • Published : 2021.12.31
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Abstract

In this paper, we propose a sentiment analysis model that improves performance on small-scale data. A sentiment analysis model for small-scale data is proposed and verified through experiments. To this end, we propose Bagging-Bi-GRU, which combines Bi-GRU, which learns GRU, which is a variant of LSTM (Long Short-Term Memory) with excellent performance on sequential data, in both directions and the bagging technique, which is one of the ensembles learning methods. In order to verify the performance of the proposed model, it is applied to small-scale data and large-scale data. And by comparing and analyzing it with the existing machine learning algorithm, Bi-GRU, it shows that the performance of the proposed model is improved not only for small data but also for large data.

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References

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