Systematic Study on Deep Learning Techniques for Prediction of Movies

T. Senthil Kumar, Anirudh Jain and Monika Kumari Sah

Deep learning has achieved great success in various fields, such as computer vision and natural language processing. It is effective as it has a strong learning ability and it can extract higher-level features from raw input. In this study, the characteristics of the movies that generate the highest revenue from given datasets have been explored. With the global presence of data in social media, it‟s a challenge to classify the conveyed mindset or feelings of viewers such as good, bad, positive, negative, thumbs up, thumbs down, etc. To overcome the issue of expressed views, sentiment analysis and deep learning techniques can be merged together. Deep learning techniques such as Natural Language Processing, Text Mining, and Learning Vector Quantization etc. allow better feature extraction which also helps the film industry to predict and choose those characteristics that lead to the highest popularity of the movie.

Volume 12 | 04-Special Issue

Pages: 31-38

DOI: 10.5373/JARDCS/V12SP4/20201463