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Survey for Movie Recommendation System: Challenge and Problem Solution

영화 추천 시스템을 위한 연구: 한계점 및 해결 방법

  • Latt, Cho Nwe Zin (Dept. of Information Security, Pukyong National University) ;
  • Aguilar, Mariz (Dept. of Information Security, Pukyong National University) ;
  • Firdaus, Muhammad (Dept. of Artificial Intelligence Convergence, Pukyong National University) ;
  • Kang, Sung-Won (Dept. of Artificial Intelligence Convergence, Pukyong National University) ;
  • Rhee, Kyung-Hyune (Division of Computer Engineering, Pukyong National University)
  • Published : 2022.05.17

Abstract

Recommendation systems are a prominent approach for users to make informed automated judgments. In terms of movie recommendation systems, there are two methods used; Collaborative filtering, which is based on user similarities; and Content-based filtering which takes into account specific user's activity. However, there are still issues with these two existing methods, and to address those, a combination of collaborative and content-based filtering is employed to produce a more effective system. In addition, various similarity methodologies are used to identify parallels among users. This paper focuses on a survey of the various tactics and methods to find solutions based on the problems of the current recommendation system.

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Acknowledgement

This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITP (Institute for Information & Communications Technology Planning & Evaluation) (IITP-2022-2020-0-01797) and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education(2021R1I1A3046590)