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@article{152068,
        author = {Ayush Pandey and Ananya Sharan  and Vibhanshu Mishra  and Richa Gupta and Ms Charu Tyagi},
        title = {Movie Recommendation System Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {2},
        pages = {336-339},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=152068},
        abstract = {This research paper represents the techniques and approaches which are used in the movie recommendation system.As we are very well aware about the fact that extracting meaningful data from the homogenous amount of raw data is a challenging problem and recommendation systems helps us in this situation. Recommendation system plays a very important role in our day to day life as it  provides suggestions  based on some data sets to users for certain resources such as movies, books, songs, etc .Recommendation systems are very fruitful for various  organizations as large amount of data is being collected from various  customers  and after extracting the data’s it  provides best suggestions. Movie  recommendation systems is  helping peoples who are fond of  watching movies by providing suggestions for what movie to go with without going  through the large set of movies data . To reduce the human efforts by  providing suggestions of  movies based on the user interest is our main moto.  Recommendation system is based on three approaches : first one is Collaborative Filtering, second one is  Content based and third one is hybrid based Approach},
        keywords = {System ,  Filtering , Approach ,  Memory based, Content based approach , Hybrid approach .  },
        month = {},
        }