The Journal of the Convergence on Culture Technology (문화기술의 융합)

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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Machine Learning Approach for Prediction of VOD Usage

머신러닝을 활용한 VOD 이용건수 예측

  • 전종석 (한동대학교 ICT창업학부) ;
  • 장하은 (한동대학교 커뮤니케이션학부) ;
  • 오주희 (한동대학교 경영경제학부)
  • Received : 2022.07.11
  • Accepted : 2022.09.09
  • Published : 2022.09.30
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Abstract

This study developed a model for predicting the number of VOD uses of IPTV, an online market in the film industry. A machine learning-based prediction model was established using the VOD usage data collected by the Korean Film Council from 2017 to 2021. Through literature research and cluster analysis, the difference between the offline market and the online market is revealed, and a new category of VOD usage is proposed. The purpose is to help IPTV companies establish marketing strategies as well as support decision-making by developing a machine learning-based VOD usage prediction model.

본 연구는 영화 산업에서 온라인 시장인 IPTV의 VOD 이용 건수 예측 모델을 개발하였다. 한국영화진흥위원회에서 수집한 2017년부터 2021년까지 VOD 이용건수 데이터를 활용하여 머신러닝 기반 예측모델을 구축했다. 문헌조사와 군집분석을 통하여 오프라인 시장과 온라인 시장의 차이를 밝히고, VOD 이용 건수의 새로운 범주를 제안한다. 머신러닝 기반의 VOD 이용 건수 예측 모델 개발을 통해 IPTV 기업들의 의사결정 지원 뿐 아니라 마케팅 전략 수립을 돕는 것을 목적으로 한다.

Keywords

Acknowledgement

본 연구는 2022년도 한동대학교 ICT기업가 정신센터 대학혁신지원사업의 지원을 받아 수행하였음.

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