Prediction of Movies popularity using machine learning techniques

The prediction of movies popularity is challenging problem. Movies prediction is a hot topic for movie makers, producers, directors, production houses and also there is a large amount of data related to the movies is available over the internet, because of that much data available, it is an interesting data mining topic. Every viewer, producer, directors, production houses all are curious about the movies that how it will perform in the theatre. In this research, we have used IMDB for our experimentation. We carried our research by predicting the rating of movie and by predicting the gross of movie before its theatrical release. In this research, we have extracted the data from IMDB, this raw data was then preprocessed, transformed, integrated and cleaned. The relevant features were selected from data set. We then performed different sets of experimentation using machine learning techniques to predict rating and gross of a movie. We tried to build an efficient model that can fairly predict the rating and gross of movies. The results are presented in bingo and 1-away accuracy. We are then able to achieve an accuracy of 99% for rating and 94% for gross. We have also compared our result with other efforts in the same research area with our results exceeding the previous studies.