Proceedings of the Korea Information Processing Society Conference (한국정보처리학회:학술대회논문집)

  • 2023.11a
  • /
  • Pages.322-326
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  • 2023
  • /
  • 2005-0011(pISSN)
  • /
  • 2671-7298(eISSN)
Korea Information Processing Society (한국정보처리학회)
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A Movie recommendation using method of Spectral Bipartition on Implicit Social Network

잠재적 소셜 네트워크를 이용하여 스펙트럼 분할하는 방식 기반 영화 추천 시스템

  • Sadriddinov Ilkhomjon (Dept. of Software Convergence, Soonchunhyang University) ;
  • Sony Peng (Dept. of Software Convergence, Soonchunhyang University) ;
  • Sophort Siet (Dept. of Software Convergence, Soonchunhyang University) ;
  • Dae-Young Kim (Dept. of Computer Software Engineering, Soonchunhyang University) ;
  • Doo-Soon Park (Dept. of Computer Software Engineering, Soonchunhyang University)
  • 일홈존 (순천향대학교 소프트웨어융합학과 ) ;
  • 펭소니 (순천향대학교 소프트웨어융합학과 ) ;
  • 싯소포호트 (순천향대학교 소프트웨어융합학과 ) ;
  • 김대영 (순천향대학교 컴퓨터소프트웨어학과 ) ;
  • 박두순 (순천향대학교 컴퓨터소프트웨어학과 )
  • Published : 2023.11.02
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Abstract

We propose a method of movie recommendation that involves an algorithm known as spectral bipartition. The Social Network is constructed manually by considering the similar movies viewed by users in MovieLens dataset. This kind of similarity establishes implicit ties between viewers. Because we assume that there is a possibility that there might be a connection between users who share the same set of viewed movies. We cluster users by applying a community detection algorithm based on the spectral bipartition. This study helps to uncover the hidden relationships between users and recommend movies by considering that feature.

Keywords

Acknowledgement

This research was supported by the National Research Foundation of Korea (No. NRF-2022R1A2C1005921) and BK21 FOUR (Fostering Outstanding Universities for Research) (No.5199990914048)