Course recommendation method, device, equipment and medium based on root cause analysis

Abstract

The present invention relates to the field of artificial intelligence, and provides a course recommendation method, device, equipment and medium based on root cause analysis, which can identify the label of each course in course data, and construct training samples for training prediction according to the label of each course and course data Model, according to the prediction model, the improved ID3 algorithm is used to calculate the information entropy of each tag, the information gain of each tag is calculated according to the information entropy of each tag, and the course recommendation list is generated according to the information gain of each tag, combined with the ID3 algorithm The root cause analysis of the impact of training courses on performance ensures the interpretability and accuracy of the analysis results, assists in the analysis of training courses that have a greater impact on performance, and then combines artificial intelligence to automatically recommend courses for continuous tracking , Improve performance and retention, so that training can truly help the team's improvement and personal development. In addition, the present invention also relates to block chain technology, and the prediction model can be stored in block chain nodes.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a course recommendation method, device, equipment and medium based on root cause analysis. Background technique [0002] Every department in the enterprise needs regular training to improve the ability of employees. However, at present, training courses can only be determined through subjective judgments. Due to the lack of understanding of the value of training courses, it is impossible to grasp the impact of training course types on performance goals. It is difficult to identify the training courses that have a greater impact on performance, and it is impossible to effectively and targetedly track the training process and evaluate the training results. [0003] In view of the above situation, in the prior art, methods such as correlation calculation are usually used to find the most valuable course, but the meaning of the recommendation result obtained b...

AI Technical Summary

Problems solved by technology

[0002] Every department in the enterprise needs regular training to improve the ability of employees. However, at present, training courses can only be determined through subjective judgments. Due to the lack of understanding of the value of training courses, it is impossible to grasp the impact of training course types on performance goals. and retention indicators, it is difficult to identify training courses that have a greater impact on performance, and it is impossible to effectively and targetedly track the training process and evaluate the training results

[0003] In view of the above situation, in the prior art, methods such as correlation calculation are usually used to find the most valuable course, but the meaning of the recommendation result obtained by this method is ambiguous, the interpretability is not strong, and only the correlation is used for calculation, The reliability of the results also needs to be improved, and the accuracy is not enough

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