Analysis of TV Film Scoring and Communication Efficiency Based on Artificial Intelligence

Abstract

The spread of TV movies has brought free participation in film reviews. Movies have brought freedom of time and space for comments. You can publish your own comments at any time without time restrictions. You can publish comments on forums, blogs, vote, and various websites, film companies, and even individuals to hold special online film competitions or film review activities. With the gradual maturity of film types, a series of subtypes such as artificial intelligence, interstellar civilization, and alien species have been derived. These contents have different emphases on type characteristics and narrative characteristics, although the subtypes of films have some common characteristics in essence. Based on artificial intelligence, this paper studies the scoring analysis and communication efficiency of TV and film. By adjusting the recommendation through user feedback, the average absolute error has been improved by 18% and the accuracy has been improved by 24%. Moreover, through four rounds of feedback, the accuracy of online computing recommendation for new users is very close to that for old users. This shows the superiority of artificial intelligence algorithm in solving the problems of cold start and complex interest recommendation. It can be predicted that artificial intelligence will become a unique cultural phenomenon. Its cultural connotation is all inclusive and worthy of continuous research and exploration by future generations. Artificial intelligence appears more and more frequently in science fiction films and presents more rich and detailed diversity and complexity.