Film preferential recommendation system and method based on implicit information scoring

Abstract

The invention provides a film preferential recommendation system and method based on implicit information scoring. The system comprises a user usage detection module, a preferential recommendation system processing module, a user log information collection processing module, a user log information storage module, an implicit information scoring querying / building / updating module, an implicit information scoring storage module and a recommendation result display module. The method is based on the introduction of each module of the system, combines the analysis of user-based historical behavior log, and proposes the calculation of the user's preference for different factors (labels, actors, directors, etc.) based on implicit information in different time periods, and performs implicitly scoring of the program for recommendation. Compared with other algorithms widely used in the recommendation system on a real dataset, the experimental results show that the average accuracy of the method is higher, and the method has certain application prospects and value, and can be applied to the online film recommendation system or other similar product systems.

Description

technical field [0001] The invention relates to a system and method for film and television selection and recommendation based on implicit information scoring. Background technique [0002] The rapid development of the mobile Internet has injected new vitality into the development of the film and television industry, and the traditional film and television industry has also begun to move closer to mobile online film and television. With the rapid increase in the number of programs, the problem of information overload has begun to emerge: it is becoming more and more difficult for users to find their favorite programs in the vast sea of ​​programs in their limited spare time, and video content providers want to attract users to continuously click to watch their programs It is also becoming more and more difficult to cultivate user consumption habits and obtain benefits. In this case, program recommendation has become a common method in the field of film and television to att...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the existing collaborative filtering technology that has serious lack of explicit scoring, does not consider the different interests and hobbies of users in different time and space, and does not provide sufficient solutions for cold start. The system and method for recommending the best movies and TV shows based on information scoring, by transferring the user's historical behavior log into the recommendation system of the present invention and using the method of the present invention to obtain a list of other online movie and TV programs that users may like from the recommendation system, thereby attracting users to watch continuously, satisfying User preferences, and increase the ratings of film and television programs and the revenue of online film and television operators, with actual commercial value

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