Level evaluation method and device based on machine learning and related equipment

Abstract

The invention relates to the technical field of artificial intelligence, and discloses a level evaluation method and device based on machine learning, computer equipment and a storage medium, and the method comprises the steps: obtaining the historical data of all users, determining the initial level of the current user as the current level based on the historical data, and based on each piece of response information and the historical data, determining a new level of the current user as an updated current level by adopting a support vector machine model, determining the number of examination questions corresponding to the updated current level by adopting a logistic regression model, and updating the examination information according to the updated current level and the number of examination questions corresponding to the updated current level. The target level of the current user is determined according to the current level and the updated answering accuracy of the current level, the current level and the question setting number corresponding to the current level are dynamically adjusted according to the real-time answering state of the user, and the real ability level of each user can be known more accurately.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a machine learning-based level evaluation method, device, computer equipment and storage medium. Background technique [0002] With the popularity of the Internet, traditional teaching methods have changed, and online education has emerged as the times require. In order to provide users with better educational services, before conducting online education, the online education platform evaluates the knowledge level of each user, and then recommends corresponding learning courses for each user based on the evaluation results. [0003] At present, the way to evaluate the user's knowledge level is mainly to use a set of test papers with fixed test questions for the user to answer, and to evaluate the user's knowledge level according to the obtained test results, and finally recommend the user according to the evaluation results. Learning courses, so that user...

AI Technical Summary

Problems solved by technology

[0003] At present, the way to evaluate the user's knowledge level is mainly to use a set of test papers with fixed test questions for the user to answer, and to evaluate the user's knowledge level according to the obtained test results, and finally recommend the user according to the evaluation results. Learning courses, so that users are evaluated only by using a set of test papers with fixed test questions, for higher-level users, the same evaluation results may be obtained, which leads to the inability to make a judgment on the knowledge level of higher-level users. Accurate judgment makes it impossible for the online education platform to accurately recommend learning courses corresponding to the user's knowledge level

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