Filin – A Movie Recommendation on Content Basis

Recommendation is important because user don’t want to waste the time in searching for the movie that he like. That’s why recommendation system play important role to get the best movie recommendation. After referring a lot of research paper, we get to know that there are various techniques for recommendation such as content- based filtering, collaborative filtering, hybrid technique etc. In this paper we use content-based filtering that recommend the movie using the past activity and past content that the user watch. The cosine similarity algorithm is used in which the single string converted into vector and then find the similarity between the vectors. You can convert it into hybrid approach by using other technique with content-based filtering.