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Prediction of Imdb Movie Rating using Datamining Techniques

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dc.contributor.advisor Guha, Sumanta
dc.contributor.author Manideep, Alimi
dc.contributor.other Anutariya, Chutiporn
dc.contributor.other Dung, Phan Minh
dc.date.accessioned 2017-07-14T07:59:30Z
dc.date.available 2017-07-14T07:59:30Z
dc.date.issued 2017-07
dc.identifier.other AIT
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/866
dc.description 45 p en_US
dc.description.abstract As we know that many thousands of movies were releasing in every year, to make a movie more budget is required and it costs a bomb about million dollars for completing a movie. To make the movie success is important to industry as they spend a lot of money in making of the film. So, in order to reduce this problem, the movie rating prediction can help us many people to select which type of the movie will become success and what the factors included in the movie. The aim is to predict the Imdb movie ratings with the pre-release attributes which includes cast and crew. Beyond many techniques only few are considered and implemented in this research study. With the available attributes, the rating can be predicted by available techniques, the techniques which we are used are k-nearest neighbor, linear regression and artificial neural net. So, after finding the accuracy of each and every model, the model with the highest accuracy can be taken for final prediction. en_US
dc.description.sponsorship AIT Fellowship en_US
dc.language.iso en_US en_US
dc.publisher AIT en_US
dc.subject movie ratings en_US
dc.subject Imdb en_US
dc.subject prediction en_US
dc.subject K- Nearest Neighbors en_US
dc.subject Artificial Neural Net en_US
dc.subject Linear Regression en_US
dc.subject accuracy en_US
dc.subject pre-release attributes en_US
dc.title Prediction of Imdb Movie Rating using Datamining Techniques en_US
dc.type Research report en_US

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