A game intelligent rating method and system

Abstract

The present invention relates to a game intelligent rating method and system. The method includes the following steps: collecting numerical data and text data of online games before going online; extracting numerical features and text features of online games before going online and performing feature processing ; According to the numerical features, text features and level labels of the online games after feature processing, the optimal random forest algorithm model is established and trained; the numerical data and text data of the offline games are collected; the offline games are extracted According to the optimal random forest algorithm model, input the numerical features and text features of games that are not online after feature processing, and predict the game level of games that are not online. The game intelligent rating method and system of the present invention have the advantages of accurate rating and not being affected by human subjective factors.

Description

technical field [0001] The invention relates to the field of game ratings, in particular to a game intelligent rating method and system. Background technique [0002] The game industry is a highly integrated field of technology and content. With the development of the economy, the iterative update of VR / AR and other new technologies and hardware and the reduction of the Engel coefficient on a global scale have endowed the game industry with new huge development potential and business opportunities. In the game industry chain, game platform operators are an important link connecting game developers and users. Game platform operators formulate operating strategies and allocate resources based on game ratings, with a view to maximizing profits in proportion to investment costs and returns. [0003] However, the existing game rating methods are usually based on the subjective judgment of the game platform operator’s evaluators based on their own cognition and experience. There...

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Problems solved by technology

[0003] However, the existing game rating methods are usually based on the subjective judgment of the game platform operator’s evaluators based on their own cognition and experience. Therefore, the game rating results will be affected by the game evaluation team’s subjective consciousness, cognitive level, The interference of human factors such as the amount of experience and the flow of personnel leads to large fluctuations in the accuracy of ratings, which will ultimately have an adverse impact on game platform operators

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