The Transactions of the Korea Information Processing Society (정보처리학회 논문지)

Korea Information Processing Society (한국정보처리학회)
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Personalized Cross-Domain Recommendation of Books Based on Video Consumption Data

영상 소비 데이터를 기반으로 한 교차 도메인에서 개인 맞춤형 도서 추천

  • 임예빈 (동덕여자대학교 정보통계학과 ) ;
  • 김현희 (동덕여자대학교 정보통계학과 )
  • Received : 2024.07.02
  • Accepted : 2024.07.22
  • Published : 2024.08.31
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Abstract

Recently, the amount of adult reading has been continuously decreasing, but the consumption of video content is increasing. Accordingly, there is no information on preferences and behavior patterns for new users, and user evaluation or purchase of new books are insufficient, causing cold start problems and data scarcity problems. In this paper, a hybrid book recommendation system based on video content was proposed. The proposed recommendation system can not only solve the cold start problem and data scarcity problem by utilizing the contents of the video, but also has improved performance compared to the traditional book recommendation system, and even high-quality recommendation results that reflect genre, plot, and rating information-based user taste information were confirmed.

최근 성인 독서량은 지속적으로 감소하는데 비해 영상 콘텐츠 소비가 증가하고 있다. 이에 따라 새로운 사용자에 대한 선호도 및 행동 패턴에 대한 정보가 없고 새로운 도서에 대한 사용자 평가나 구매 정보가 부족해 콜드 스타트 문제와 데이터 희소성 문제가 발생하고 있다. 본 논문에서는 영상물 콘텐츠 기반 도서 하이브리드 추천 시스템을 제안하였다. 제안하는 추천 시스템은 영상물의 콘텐츠를 활용하여 콜드 스타트 문제와 데이터 희소성 문제를 해결할 수 있을 뿐만 아니라, 전통적인 도서 추천 시스템에 비해 성능이 향상됨을 보여주었다. 또한 장르, 줄거리, 평점 정보 등 사용자 취향 정보까지 모두 반영한 개인 맞춤형 추천 결과를 제시하였다.

Keywords

References

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