• DocumentCode
    2546022
  • Title

    Movie Recommendation System Based on Movie Swarm

  • Author

    Halder, Sebastian ; Sarkar, A. M. Jehad ; Young-Koo Lee

  • Author_Institution
    Dept. of Comput. Eng., Kyung Hee Univ., Yongin, South Korea
  • fYear
    2012
  • fDate
    1-3 Nov. 2012
  • Firstpage
    804
  • Lastpage
    809
  • Abstract
    A movie recommendation is important in our social life due to its strength in providing enhanced entertainment. Such a system can suggest a set of movies to users based on their interest, or the popularities of the movies. Although, a set of movie recommendation systems have been proposed, most of these either cannot recommend a movie to the existing users efficiently or to a new user by any means. In this paper we propose a movie recommendation system that has the ability to recommend movies to a new user as well as the others. It mines movie databases to collect all the important information, such as, popularity and attractiveness, required for recommendation. It generates movie swarms not only convenient for movie producer to plan a new movie but also useful for movie recommendation. Experimental studies on the real data reveal the efficiency and effectiveness of the proposed system.
  • Keywords
    data mining; database management systems; entertainment; recommender systems; movie attractiveness information; movie database mining; movie popularity information; movie recommendation system; movie swarm; Clustering algorithms; Collaboration; Computers; Data mining; Educational institutions; Filtering; Motion pictures; Interesting movie; movie swarm; popular movie; recommendation system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud and Green Computing (CGC), 2012 Second International Conference on
  • Conference_Location
    Xiangtan
  • Print_ISBN
    978-1-4673-3027-5
  • Type

    conf

  • DOI
    10.1109/CGC.2012.121
  • Filename
    6382910