Method for knowledge points diagnosis based on influence factors and neural networks

An impact factor, neural network technology, applied in the computer field, can solve problems such as unreliable conclusions, long time, and poor user experience.

Inactive Publication Date: 2017-05-31
FUZHOU ROCKCHIP SEMICON
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Problems solved by technology

[0005] To this end, it is necessary to provide a knowledge point identification method based on impact factors and neural networks. This method extracts the impact factors related to whether the user has mastered a certain knowledge point, and inputs the impact factors into the trained multi-layer neural network. I

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  • Method for knowledge points diagnosis based on influence factors and neural networks
  • Method for knowledge points diagnosis based on influence factors and neural networks
  • Method for knowledge points diagnosis based on influence factors and neural networks

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[0070] In order to explain in detail the technical content, structural features, achieved goals and effects of the technical solution, the following will be described in detail in conjunction with specific embodiments and accompanying drawings.

[0071] see figure 2 , a flow chart of the method for identifying knowledge points based on impact factors and neural networks according to an embodiment of the present invention. The method comprises the steps of:

[0072] First enter step S201 to quantify the impact factors of knowledge points, and establish a multi-layer neural network model according to the quantified impact factors. In this embodiment, the influencing factors of the knowledge points include the user's overall quality, the user's family education level, the user's school education level, the user's social education level, and subjects.

[0073] The present invention is aimed at the specified subject knowledge, so the classification of "subject" is one of the inf...

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Abstract

The invention provides a method for knowledge points diagnosis based on influence factors and neural networks. By means of the method for knowledge points diagnosis based on influence factors and neural networks, the network parameters of the convergent neural network model are preserved through the refined influence factors and the designed multi-layer neural network model after training offline. During the knowledge points diagnosis process, the influence factors related to the knowledge points to be tested of the user to be tested can be input into the trained neural network model to directly know the grasping situation of the knowledge of the user by means of the calculation of the algorithm, therefore, the knowledge points diagnosis of the user can be performed quickly. Compared with the original way of doing exercise, the method for knowledge points diagnosis based on influence factors and neural networks has the following advantages: the duration of the diagnosis is greatly shortened, the efficiency is improved, and the user experience is effectively enhanced. The method for knowledge points diagnosis based on influence factors and neural networks has broad market prospect.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a method for identifying knowledge points based on impact factors and neural networks. Background technique [0002] Understanding knowledge points has always been a hot issue in the online education system of primary and secondary schools, and is an integral part of the entire online education system. By investigating the knowledge points of new users, it is possible to roughly determine which knowledge points a user has mastered and which ones have not. Only in this way can we recommend different learning materials to different users in a targeted manner, so as to provide personalized guidance to users and effectively improve their learning performance. Therefore, how to effectively understand the knowledge points of newly registered users is particularly important in the entire online education system. [0003] At present, the method of finding out the knowledge points of ...

Claims

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Application Information

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IPC IPC(8): G06N3/04G06N3/08G06Q50/20
CPCG06N3/084G06Q50/205G06N3/044
Inventor 纪大峣
Owner FUZHOU ROCKCHIP SEMICON
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