Film evaluation prediction method and system

Abstract

The invention discloses a film evaluation prediction method and system. The method comprises the steps of firstly selecting characteristics of film data set for training through a sequential forward selection method, and conducting de-noising, pre-processing and extracting of a characteristic vector; secondly collecting rating information corresponding to each film, and conducting normalization processing of all the ratings to obtain a rating distribution vector; thirdly, training a maximum interval rating distribution model based on the film characteristic vector and the rating distribution vector, and conducting deformation optimization to obtain a final parameter model for film rating prediction; and fourthly, extracting a characteristic vector of a film to be released, obtaining a vector by using the obtained parameter model for rating distribution prediction, conducting normalization processing of the vector, and obtaining the predicted result of the rating distribution of audience after the film is released. According the invention, the model for film rating distribution prediction can be quickly and effectively trained, and the accuracy of prediction is substantially higher than that by using existing methods.

Description

technical field [0001] The invention relates to pattern recognition and machine learning, in particular to a film evaluation prediction method and system thereof. Background technique [0002] Movie evaluation prediction is based on the basic data information of an unreleased movie, such as actors, directors, distribution companies, budget, etc., to estimate the distribution of public ratings for the movie after it is released. The film industry is a global mature industry with a scale of tens of billions of dollars. Thousands of movies are released every year around the world, but only a handful of them are successful. For movie investors and distributors, the increasing shooting costs and increasingly fierce competition environment have greatly increased the investment risk of movies; more and more difficult. Therefore, it becomes very important to be able to reliably predict the public's perception of the film in the early stage of the film's release, even in the plann...

AI Technical Summary

Problems solved by technology

For movie investors and distributors, the increasing shooting costs and increasingly fierce competition environment have greatly increased the investment risk of movies; more and more difficult

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