Comparative Analysis: Machine Learning Usage Across Recommender Systems of OTT Platforms
DOI:
https://doi.org/10.58213/vidhyayana.v8i5.689Keywords:
Machine Learning, OTT (over the top), Recommendation System (RS), Collaborative FilteringAbstract
In today’s world, OTT (Over the Top) platforms have become an important factor in terms of entertainment and a major stress reliever for people all around the world. The growth of OTT platforms has been increasing day by day i.e., almost 50 percent. Millennial customers, who grew up in a digital world and don't have the time or the patience for films, television programs, or any other content to broadcast on television, will be the largest audience for streaming television. Netflix, Spotify, Amazon Prime, and Disney+Hotstar are a few entertainment platforms.
This paper aims at performing the comparative study of machine learning implementation across various OTT platform’s recommender systems by discussing the benefits of leveraging machine learning potentials to overcome the existing challenges being faced by these platforms. Also, we discuss the scope of improvising the features of OTT platforms through Machine learning approaches that could bring more value to the platform users and owners.
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