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)
Proceedings of the Korea Information Processing Society Conference (한국정보처리학회:학술대회논문집)
- 2023.05a
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- Pages.389-391
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- 2023
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- 2005-0011(pISSN)
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- 2671-7298(eISSN)
DOI QR Code
Movie Recommendation System using Community Detection and Parallel Programming
커뮤니티 탐지 및 병렬 프로그래밍을 이용한 영화 추천 시스템
- Sadriddinov Ilkhomjon (Dept. of Software Convergence, Soonchunhyang University) ;
- Yixuan Yang (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 ) ;
- 양예선 (순천향대학교 소프트웨어융합학과) ;
- 펭소니 (순천향대학교 소프트웨어융합학과) ;
- 싯소포호트 (순천향대학교 소프트웨어융합학과 ) ;
- 김대영 (순천향대학교 컴퓨터소프트웨어학과 ) ;
- 박두순 (순천향대학교 컴퓨터소프트웨어학과 )
- Published : 2023.05.18
Abstract
In the era of Big Data, humanity is facing a huge overflow of information. To overcome such an obstacle, many new cutting-edge technologies are being introduced. The movie recommendation system is also one such technology. To date, many theoretical and practical kinds of research have been conducted. Our research also focuses on the movie recommendation system by implementing methods from Social Network Analysis(SNA) and Parallel Programming. We applied the Girvan-Newman algorithm to detect communities of users, and a future package to perform the parallelization. This approach not only tries to improve the accuracy of the system but also accelerates the execution time. To do our experiment, we used the MovieLense Dataset.
Keywords