CONTENT BASED MOVIE RECOMMENDING SYSTEM

Information Technology

In the current era, most people are habituated to watching movies. Different people aspire to watch different genres of movies. So, the primary goal of movie recommendation systems is to filter and predict only those movies that a corresponding user is most likely to watch. In this, a web application is built to recommend five movies respective to the given movie using a machine learning model which converts content data to vectors and finds the similarity between movies through the angle between each vector. In this project, we used a content-based movie recommendation system. Content-based systems use metadata such as genre, producer, actor, and musician to recommend items say movies or music. Such a recommendation would be for instance recommending Infinity War which featured Vin Diesel because someone watched and liked The Fate of the Furious. Similarly, you can get music recommendations from certain artists because you liked their music. Content-based systems are based on the idea that if you liked a certain item, you are most likely to like something like it.

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