Movie Popularity Classification based on Inherent Movie Attributes using C4.5, PART and Correlation Coefficient

Khalid Ibnal Asad, Tanvir Ahmed, Md. Saiedur Rahman

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

11 Citations (Scopus)
514 Downloads (Pure)

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.S and PART classifier algorithm and define the relation between attributes of post release movies using correlation coefficient.
Original languageEnglish
Title of host publicationInformatics, Electronics & Vision (ICIEV), 2012 International Conference on
Number of pages6
PublisherIEEE
Publication dateMay 2012
Pages747-752
ISBN (Print)978-1-4673-1153-3
DOIs
Publication statusPublished - May 2012
EventInformatics, Electronics & Vision (ICIEV), 2012 International Conference on - Dhaka, Bangladesh
Duration: 18 May 201219 May 2012

Conference

ConferenceInformatics, Electronics & Vision (ICIEV), 2012 International Conference on
CountryBangladesh
CityDhaka
Period18/05/201219/05/2012

Keywords

  • C4.5
  • IMDB
  • PART
  • Data Mining
  • Movie

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