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2018 | OriginalPaper | Chapter

Genre Fraction Detection of a Movie Using Text Mining

Authors : Sunil Saumya, Jitendra Kumar, Jyoti Prakash Singh

Published in: Advanced Computing and Systems for Security

Publisher: Springer Singapore

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Abstract

Movie genre plays a significant role in recommendation system as everyone has a liking for movies of specific genres. Nowadays, a Wikipedia (or wiki) page or plot for each movie is maintained on the Web. In this chapter, we propose to use the Wikipedia movie plot for genre fraction detection using text mining techniques. For our purpose, we use the bag-of-words model as topic modeling where the (frequency of) occurrence of each word is used as a feature for training a classifier. We create the corpus for 20 genres with word frequencies 1, 5, and 15 separately. Wikipedia movie plot of 640 movies is used to evaluate the proposed system. A total of 540 movie plots are used for creating corpuses, and the rest 100 are used as a test set. The system performs best on refined corpus with word frequency 15.

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previous chapter Optimum Circle Formation by Autonomous Robots
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Metadata
Title
Genre Fraction Detection of a Movie Using Text Mining
Authors
Sunil Saumya
Jitendra Kumar
Jyoti Prakash Singh
Copyright Year
2018
Publisher
Springer Singapore
Book
Advanced Computing and Systems for Security

Print ISBN: 978-981-10-8179-8

Electronic ISBN: 978-981-10-8180-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-8180-4_11

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