Bayesian network based Music Recommendation System considering Multi-Criteria Decision Making

다기준 의사결정 방법을 고려한 베이지안 네트워크 기반 음악 추천 시스템

  • 김남국 (공주대학교 컴퓨터공학과 컴퓨터소프트웨어 전공) ;
  • 이상용 (공주대학교 컴퓨터공학부)
  • Received : 2013.01.30
  • Accepted : 2013.03.20
  • Published : 2013.03.31


The demand and production for mobile music increases as the number of smart phone users increase. Thus, the standard of selection of a user's preferred music has gotten more diverse and complicated as the range of popular music has gotten wider. Research to find intelligent techniques to ingeniously recommend music on user preferences under mobile environment is actively being conducted. However, existing music recommendation systems do not consider and reflect users' preferences due to recommendations simply employing users' listening log. This paper suggests a personalized music-recommending system that well reflects users' preferences. Using AHP, it is possible to identify the musical preferences of every user. The user feedback based on the Bayesian network was applied to reflect continuous user's preference. The experiment was carried out among 12 participants (four groups with three persons for each group), resulting in a 87.5% satisfaction level.


Bayesian network;AHP;Music Recommendation;Personalized service;Recommendation System


Supported by : 한국연구재단