Personalized test question recommendation method based on knowledge graph

A technology of knowledge graph and recommendation method, applied in the field of smart education recommendation, can solve the problem that the relationship between knowledge points of recommended test questions cannot be taken into account, and achieve the effect of good expansion performance.

Pending Publication Date: 2021-07-16
XIAN UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a method for recommending personalized test questions based on knowledge graphs, which solve

Method used

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  • Personalized test question recommendation method based on knowledge graph
  • Personalized test question recommendation method based on knowledge graph
  • Personalized test question recommendation method based on knowledge graph

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Embodiment

[0092] A personalized test question recommendation method based on knowledge graph, the process is as follows figure 1 As shown, the specific steps are as follows:

[0093] Step 1, construct the knowledge map of the corresponding field

[0094] According to the recommended object, select the electronic textbook of the corresponding knowledge field to construct the ontology structure of the knowledge point, and then manually extract the entities, relationships and attributes in the ontology structure to realize the preliminary construction of the knowledge map, and then manually construct the knowledge map of the corresponding field from top to bottom;

[0095] Specifically:

[0096] Step 1.1, select the corresponding knowledge field according to the recommended object, and classify the electronic textbooks in the corresponding knowledge field according to three layers. The chapter is the first layer, the section is the second layer, and the meta-knowledge is the third layer. ...

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Abstract

The invention discloses a personalized test question recommendation method based on a knowledge graph, and the method specifically comprises the steps: constructing the knowledge graph, crawling test questions in a corresponding field in a network as a test question bank, carrying out the manual analysis of knowledge points inspected by the test questions in the test question bank, enabling the test questions to correspond to the knowledge graph, and enabling the examination knowledge points to correspond to the test questions; mapping a personalized knowledge sub-graph of each learner according to the learning target and the knowledge graph of the learner; obtaining the current cognitive level of the knowledge points of the learner; calculating the intimacy of the knowledge points; and realizing personalized test question recommendation based on the cognitive level of the learner on the target knowledge point and the intimacy of the knowledge point. According to the personalized test question recommendation method based on the knowledge graph, the problem that the relationship between knowledge points corresponding to recommended test questions cannot be considered in the prior art is solved.

Description

technical field [0001] The invention belongs to the technical field of recommendation methods for smart education, and relates to a method for recommending personalized test questions based on knowledge graphs. Background technique [0002] With the continuous development of Internet big data, online education and smart education have developed rapidly, and recommendation systems have also sprung up. Online education breaks the constraints of time and space and effectively improves students' learning efficiency. These recommendation systems provide students with a large number of practice test questions to help students test and consolidate their knowledge. In the era of data explosion, facing the vast amount of test question resources, it is impossible for students to practice all relevant test questions within a limited time. How to make students practice test questions suitable for individual cognitive level and development within a limited time is an important research...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06F16/36G06N5/02G06Q50/20
CPCG06F16/9535G06F16/367G06N5/022G06Q50/205
Inventor 王磊党小春
Owner XIAN UNIV OF TECH
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