Open AccessDesign of a Movie Review Rating Prediction (MR2P) Algorithm
Author(s) -
Oluwatofunmi Adetunji,
Mamudu Hadiza,
Nzechukwu C. Otuneme
Publication year - 2020
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit206461
Subject(s) - film industry , entertainment industry , entertainment , profit (economics) , work (physics) , crew , computer science , marketing , advertising , algorithm , artificial intelligence , engineering , business , economics , movie theater , art , visual arts , microeconomics , mechanical engineering , aeronautics
Entertainment is no longer just anything that we enjoy occasionally, with over two million spectators a day, the amount generated by the movie industry is huge. The movie sector is one of the biggest contributors to the entertainment industry’s unpredictability in success and failure. The aim of this research work to design an efficient movie recommendation algorithm that will increase prediction accuracy, the Movie Review Rating Prediction (MR2P) was achieved through a systematic review of the existing movie success algorithm. This research work will enable movie stakeholders (producers, directors, crew, cast already in the movie industry or aspirants) to know the kind of movie to invest in which will, in turn, be beneficial in terms of higher profit.