Movie production investment decision system
| Autor: | Ankit A. Sinha, Rajashree Shedge, Avi Sinha, S. V. Vamsi Krishna |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
05 social sciences 02 engineering and technology Film industry Profit (economics) Random forest Market research Investment decisions Decision system 020204 information systems 0502 economics and business Personal choice 0202 electrical engineering electronic engineering information engineering 050211 marketing Marketing business |
| Zdroj: | 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS). |
| DOI: | 10.1109/icecds.2017.8390215 |
| Popis: | Indian movie industry produces over 100 movies per year. However, very few movies taste success and make valuable profit. Nowadays, the decision of selecting any movie to produce is mostly dependent on the personal choice of the production head. Many important factors such as target demographic, visual effects (VFX) requirements, adaption factor, etc. are not considered. All these factors also contribute towards the success of any movie and thus should not be overlooked. Given the low success rate, models, and mechanisms to predict reliably the probability of the movie's success can help de-risk the business significantly for production houses who invest huge amount of money in these movies. The proposed project uses Random Forest Classification for predictive analysis based on various factors for calculating the probability of the movie's success, hereby, help production houses to make better investment decisions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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