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
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