Course recommendation method and device based on unsupervised learning, equipment and medium

Abstract

The invention relates to the field of artificial intelligence, and provides a course recommendation method and device based on unsupervised learning, equipment and a medium, which can adopt a cycle-GAN model to extend training data, effectively solve the problems of poor model training effect and poor precision caused by insufficient samples, and meanwhile, improve the accuracy of the training data due to the characteristics of the cycle-GAN model. In addition, the samples generated after expansion have high availability, and the recommended courses are more reasonable due to the fact that prediction results of different dimensions are integrated, so that the courses are automatically recommended. The invention also relates to a blockchain technology, and the involved model can be stored in the blockchain.

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 unsupervised learning. Background technique [0002] At present, the training for the sales department lacks flexibility and can only provide standardized and standardized training content, which cannot meet the actual needs of the sales department, sales team and agents. Specifically, the business objectives of the sales department and agents mainly include sales, main development, business development, and staff increase. Setting up targeted business training will greatly improve their business performance, such as billing and staff increase efficiency. But the current situation is that the effect of the current sales department training is difficult to guarantee. [0003] In addition, the characteristic of agents with thousands of faces also adds difficulty to the training planning o...

AI Technical Summary

Problems solved by technology

But the current situation is that the effect of the current sales department training is difficult to guarantee

[0003] In addition, the characteristics of agents with thousands of faces also add difficulties to the training planning of the sales department

On the one hand, it is difficult to abstractly summarize the training needs that can match the overall situation of the sales department, and design and implement the training plan according to the training needs; Customize appropriate training objectives and directions

[0004] Moreover, the training effect of the commonly used course recommendation model is also limited to the number of training samples. When there are not enough samples to support the model for training, the effect of model prediction will be greatly affected

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