Prediction of IMDb movie rating using data-mining techniques | |
| Author | Manideep, Alimi |
| Call Number | AIT RSPR no.IM-17-04 |
| Subject(s) | Data mining--Computer programs Motion pictures--Databases |
| Note | A research submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Research studies project report ; no. IM-17-04 |
| Abstract | As we know that many thousands of movies were releasing in the 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 castandcrew. 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 artificia lneural net. So after finding the accuracy of each and every model, the model with the highest accuracy can be taken for final prediction. |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Research studies project report ; no. IM-17-04 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Information Management (IM) |
| Chairperson(s) | Sumanta Guha; |
| Examination Committee(s) | Phan Minh Dung;Chutiporn Anutariya; |
| Scholarship Donor(s) | Royal Thai Government Fellowship; |
| Degree | Research studies project report (M. Sc.) - Asian Institute of Technology, 2017 |