International Journal of Internet, Broadcasting and Communication

  • 제13권2호
  • /
  • Pages.173-178
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  • 2021
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  • 2288-4920(pISSN)
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  • 2288-4939(eISSN)
한국인터넷방송통신학회 (The Institute of Internet, Broadcasting and Communication)
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Korean Sentiment Analysis Using Natural Network: Based on IKEA Review Data

  • Sim, YuJeong (Graduate School of Smart Convergence Kwangwoon University) ;
  • Yun, Dai Yeol (Department of information and communication Engineering, Institute of Information Technology, Kwangwoon University) ;
  • Hwang, Chi-gon (Department of Computer Engineering, Institute of Information Technology, Kwangwoon University) ;
  • Moon, Seok-Jae (Department of Artificial Intelligence, Institute of Information Technology, KwangWoon University)
  • 투고 : 2021.03.21
  • 심사 : 2021.03.28
  • 발행 : 2021.05.31
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초록

In this paper, we find a suitable methodology for Korean Sentiment Analysis through a comparative experiment in which methods of embedding and natural network models are learned at the highest accuracy and fastest speed. The embedding method compares word embeddeding and Word2Vec. The model compares and experiments representative neural network models CNN, RNN, LSTM, GRU, Bi-LSTM and Bi-GRU with IKEA review data. Experiments show that Word2Vec and BiGRU had the highest accuracy and second fastest speed with 94.23% accuracy and 42.30 seconds speed. Word2Vec and GRU were found to have the third highest accuracy and fastest speed with 92.53% accuracy and 26.75 seconds speed.

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참고문헌

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