A method and system for online training based on natural language

Abstract

The invention belongs to the technical field of natural language processing, and provides a method and system for online training based on natural language, including collecting text information of users' chatting process in real time, obtaining word vectors and sentence vectors of text information; based on word vectors and sentence vectors, Obtain the user's training intention; guide the user to enter the training mode, and obtain the user's answer corresponding to the training question; match the user's answer based on the standard answer of the training question, and calculate the score of the user's answer. Through online training based on natural language, users' training needs are discovered, and targeted training and evaluation are carried out to replace the existing manual training or machine training methods. On the one hand, the cost of training is reduced, and on the other hand, the efficiency of training is improved. Enhanced training effectiveness.

Description

technical field [0001] The invention belongs to the technical field of natural language processing, in particular to a method and system for online training based on natural language. Background technique [0002] In enterprise management, in order to improve the work proficiency of employees, enterprises need to evaluate and train each employee's professional skills in a timely manner. Now it seems that the traditional manual training method has a series of problems such as high training cost, single training plan, difficult personalization of training progress, and difficult evaluation of training results. [0003] With the development of artificial intelligence technology, the use of dialogue robots (also known as chat systems, or question-and-answer systems) to replace traditional manual training has reduced training costs to a certain extent. At present, these artificial intelligence-based dialogue robots can understand natural language from users to a certain extent t...

AI Technical Summary

Problems solved by technology

[0007] Based on the above analysis, it can be seen that the dialogue robot in the prior art has certain deficiencies when it is applied to the training scene. It cannot actively identify the user's training intention, which leads to a decrease in the efficiency of user training, and the inability to reasonably evaluate the user's training results leads to the failure of the user. The progress of training cannot be tracked, which will reduce the effect of training through the machine dialogue system to a certain extent

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