Abstract
Abstract: The internet has widened the horizons of numerous areas to engage and share relevant information in recent years. As it is said, everything has its advantages and disadvantages, thus with the increase in the field comes data saturation and data extraction difficulties. The suggestion system is critical in overcoming this challenge. Its purpose is to improve the user's experience by providing quick and comprehensible suggestions. Because of its ability to provide improved amusement, a movie suggestion is vital in our personal interaction. Users might be recommended a collection of movies depending on their interests or the appeal of the films. A recommendation system is being used to make suggestions for things to buy or see. They comb through a big database of information to lead people to the things that can suit their demands. A recommender system, also known as a recommendation engine or platform, is a type of data filtering system that attempts to forecast a user's "rating" or "preference" for an item. They're mostly employed for business purposes. This project outlines a method for providing users with generic options based on film popularity and/or theme.
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