• DocumentCode
    3508923
  • Title

    Movie popularity classification based on inherent movie attributes using C4.5, PART and correlation coefficient

  • Author

    Asad, Khalid Ibnal ; Ahmed, Tanvir ; Rahman, Md Saiedur

  • Author_Institution
    Dept. of CS, AIUB, Dhaka, Bangladesh
  • fYear
    2012
  • fDate
    18-19 May 2012
  • Firstpage
    747
  • Lastpage
    752
  • Abstract
    Abundance of movie data across the internet makes it an obvious candidate for machine learning and knowledge discovery. But most researches are directed towards bi-polar classification of movie or generation of a movie recommendation system based on reviews given by viewers on various internet sites. Classification of movie popularity based solely on attributes of a movie i.e. actor, actress, director rating, language, country and budget etc. has been less highlighted due to large number of attributes that are associated with each movie and their differences in dimensions. In this paper, we propose classification scheme of pre-release movie popularity based on inherent attributes using C4.5 and PART classifier algorithm and define the relation between attributes of post release movies using correlation coefficient.
  • Keywords
    Internet; cinematography; data mining; learning (artificial intelligence); pattern classification; recommender systems; C4.5; Internet sites; PART; bipolar classification; classification scheme; correlation coefficient; director rating; inherent movie attributes; knowledge discovery; machine learning; movie popularity classification; movie recommendation system; post release movies; prerelease movie popularity; C4.5; IMDB; PART; correlation coefficient; data mining; movie;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Informatics, Electronics & Vision (ICIEV), 2012 International Conference on
  • Conference_Location
    Dhaka
  • Print_ISBN
    978-1-4673-1153-3
  • Type

    conf

  • DOI
    10.1109/ICIEV.2012.6317401
  • Filename
    6317401