MRML-Movie Recommendation Model with Machine Learning Techniques

Ravi Gorli, Bagusetty Ajay Ram

Abstract: In the traditional days people use to visit theaters to watch movies. Some of the reviews used to give some view to visit which movie in what kind of theater and so on. According to the reviews and rating people use to visit the theaters and enjoy the movie. Some movies used to run in theaters for many days like starting with 50, 100 to 365 days and so on. Depending on various suggestions the theater owners use to predict the best movie in several aspects like actors, directors, story, songs and many other factors. In the present days it is very hard to see that a single movie is not in any theater for at least 20 to 50 days. OTT has done a lot for replace the platform for movie lovers. Within 10 to 30 days every movie is entering into the OTT platform as a lot of users are increased for the OTT. Different OTT platforms such as Amazon prime, Netflix, Hot star, Zee cinema, have attracted a lot of movie lovers where they are providing databases from past old movies to the present new movies. New movie rights are brought by many of them in a competitive way. Along with movies they are casting several daily serials, web series and different live streaming also. All the databases are maintained by each of them with high performance servers and attracting the users with reasonable subscription charges.

Keywords: Movie, Review, Automation, Subscription, OTT

How to Cite?: Ravi Gorli, Bagusetty Ajay Ram, "MRML-Movie Recommendation Model with Machine Learning Techniques", Volume 12 Issue 5, May 2023, International Journal of Science and Research (IJSR), Pages: 298-302, https://www.ijsr.net/getabstract.php?paperid=SR23322101301, DOI: https://dx.doi.org/10.21275/SR23322101301