Published Paper Details:

The recommendation system plays a crucial part in the current day and employed by many famous apps. The recommendation system has created the gathering of applications, producing a global community, and growing for plentiful knowledge. The recommendation system developed into sCollaborative Filtering, Content-based, and hybrid-based techniques. It is essential to provide the user with movie recommendations so that the user does not have to spend a significant amount of time searching for content that they would like. As a result, the function of the movie recommendation system is quite important in order to acquire user-specific movie choices. After doing considerable research on the internet and consulting a large number of scholarly articles, we came to the conclusion that the suggestions generated by Collaborative Filtering only use a single method for converting text to vectors and only use a single method for determining the degree to which vectors are similar to one another. Our project's goal is to create a recommendation engine that responds to the user in order to obtain ideas for a movie.