Published Paper Details:

Movies play important role in our life. It is one of the source of entertainment that we see in our day to day life. Which movie we really like to watch it depends on people, either it is comedy, romantic, action, adventure etc. But the problem is to find the appropriate content, because every year a lot of contents has been released. So, it is very difficult to find our favorite movie. The aim of this project is to enhance the performance and accuracy of the regular filtering technique. There are various methods which are used to implement a recommendation system. In this paper Content-based filtering and Collaborative filtering methods are used. The Content-based filtering method is takes input from the users, analyze the user�s history/past behavior and recommend a list of similar movies. In this paper, K-NN algorithms and collaborative filtering are also used to intensify the accuracy of result. In this paper, cosine similarity is used to find the similar content quickly. The cosine similarity is used as the accuracy of cosine angle. By all of this, People can find their favorite movie content easily.