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
Link To Document :
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