IMDB MOVIE ANALYSIS RECOMMENDATION ALONG WITH COMPUTER VISION
Author(s):
K Hari Charan, Chethan Reddy C V, K Sukanya, R Chidvi, Narayana H M
Keywords:
IMDB MOVIE ANALYSIS RECOMMENDATION ALONG WITH COMPUTER VISION
Abstract
The showcasing entertainment industry is known as the most powerful and impactful industries in the world. We all consume movies, tv shows, docuseries… all of us are contributors to the global success of the industry. As big as it is, it also creates different feelings and opinions on the public. Some people love a certain movie, while others may dislike it. It is what it is, we all have different tastes, we all have our preferences and that is why the industry must keep reinvent itself. Actors and actresses need to constantly push themselves to be more versatile, writers and producers must study ways of improving the quality of their movies… it is a process in constant development. Nowadays, people are more demanding than ever. With the insane amount of movie production on the market, it is also very easy for us, consumers, to jump from a movie to another, from a series to another. So, the decision factors for any of us to choose a certain movie to watch are many times in the details. Details maybe how exciting a trailer is, if it was shot in a certain country, the sound effects on the trailer, which company produced it, which actors and actresses are in… (Computer vision can be a great tool to help us understand the importance of this features) Through the IMDb data base, it is possible to develop analysis and understand what might influence the ratings. Regression models, convolutional neural network and keras models are examples of possible paths in order to explain the dependent variable (movie rating).
Article Details
Unique Paper ID: 160157

Publication Volume & Issue: Volume 9, Issue 12

Page(s): 1368 - 1372
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