International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 74 - Number 9 |
Year of Publication: 2013 |
Authors: Debaditya Barman, Nirmalya Chowdhury |
10.5120/12916-9935 |
Debaditya Barman, Nirmalya Chowdhury . Movie Business Trend Prediction using Market Basket Analysis. International Journal of Computer Applications. 74, 9 ( July 2013), 38-46. DOI=10.5120/12916-9935
Trend analysis can be defined as a process of comparing past business data to identify any significant, consistent results or trends. It is very useful method to understand any business's performance. Successful business trend analysis can take business to the right direction. Film industry is the most important component of Entertainment industry. Profit and loss both are very high for this business. A large amount of money invested in this high risk industry. Before release of a particular movie, if the Production House gets any type of business trend prediction about how the film will do business, it can be helpful to reduce the risk. It is a known fact that viewer's taste in movies can change time to time. For instance in 2009, most profitable movie in USA was New Moon (1319. 422%) which belongs to Adventure, Drama and Fantasy genres. So, profitable trend determination by movie genre analysis can be helpful for making business decisions like marketing strategy, advertising strategy etc. In this work we have tried to determine and predict the trend in movie business by analyzing movie genres. Film genres find both academic and practical applications as films can be categorized by genre at every stage of their existence, from the initial approach the screenwriter takes, to where they end up on the shelves of our local store, to how their impact on cultural history is assessed. There is also a lot of commercial interest in the way people classify and choose to watch movies — this is very important for the initial marketing of a movie, and for companies like Netflix or LoveFilm, who rely on genre categories to help their customers make their picks.