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Reseach Article

Automated Movie Genre Classification with LDA-based Topic Modeling

by Brandon Chao, Ankit Sirmorya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 13
Year of Publication: 2016
Authors: Brandon Chao, Ankit Sirmorya
10.5120/ijca2016910822

Brandon Chao, Ankit Sirmorya . Automated Movie Genre Classification with LDA-based Topic Modeling. International Journal of Computer Applications. 145, 13 ( Jul 2016), 1-5. DOI=10.5120/ijca2016910822

@article{ 10.5120/ijca2016910822,
author = { Brandon Chao, Ankit Sirmorya },
title = { Automated Movie Genre Classification with LDA-based Topic Modeling },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 13 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume145/number13/25335-2016910822/ },
doi = { 10.5120/ijca2016910822 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:48:41.949360+05:30
%A Brandon Chao
%A Ankit Sirmorya
%T Automated Movie Genre Classification with LDA-based Topic Modeling
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 13
%P 1-5
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Movie genre classification is a challenging problem with many potential applications. Whereas many prior approaches rely on image, audio, or motion features to classify movies, we consider using textual content analysis instead, which is a comparatively less computationally expensive and time consuming process. In this paper, we present a novel system for movie genre classification that uses probabilistic topic modeling of the movie’s script as its main component. Our approach uses latent Dirichlet allocation, a topic modeling algorithm, to train our model and discover common themes present in movie scripts of the same genre. We then compute the cosine similarity of the feature vectors from our trained and test models and use this value to identify the movies’ genres.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Video Genre Identification Latent Dirichlet Allocation LDA