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Predicting Movie Success with Machine Learning and Visual Analytics
| Content Provider | Semantic Scholar |
|---|---|
| Author | Omenitsch, Philipp |
| Copyright Year | 2014 |
| Abstract | Predicting a movie’s opening success is a difficult problem, since it does not always depend on its quality only. External factors such as competing movies, time of the year and even weather influence the success as these factors impact the BoxOffice sales for the moving opening. Nevertheless, predicting a movie’s opening success in terms of BoxOffice ticket sales is essential for a movie studio, in order to plan its cost and make the work profitable. I introduce a simple solution for predicting movie success in terms of financial success and viewer recipience. As a result, this approach achieved decent estimations, allowing theatre planning to a certain extent, even for small studios. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.cvast.tuwien.ac.at/sites/default/files/bakkarbeit/omenitsch.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |