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Self-adaptive learning method based on graph search algorithm and computer learning system

A technology of self-adaptive learning and learning system, applied in the field of self-adaptive learning methods and computer systems based on graph search algorithms, can solve the problems of redundant data storage, inability to support external indexes, waste of storage space, etc., to improve learning Efficiency, High Availability, Support Available Effects

Inactive Publication Date: 2019-07-19
SHANGHAI SQUIRREL CLASSROOM ARTIFICIAL INTELLIGENCE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] 1) It is necessary to pre-design the table structure, that is, the design of the schema, and the cost of later modification is relatively high;
[0006] 2) Using SQL statements to implement algorithms related to graph search is very complex, difficult, and not easy to debug;
[0007] 3) There are many redundant information for data storage, which wastes storage space;
[0008] 4) The scalability is weak, and it will not be applicable when the data volume exceeds 100 million scale;
[0009] 5) Cannot support external indexes

Method used

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  • Self-adaptive learning method based on graph search algorithm and computer learning system
  • Self-adaptive learning method based on graph search algorithm and computer learning system
  • Self-adaptive learning method based on graph search algorithm and computer learning system

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Experimental program
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Embodiment 1

[0052] like figure 1 As shown, the present embodiment provides an adaptive learning method based on a graph search algorithm, comprising the following steps:

[0053] 1) Establish a knowledge map and store the knowledge map in the graph database;

[0054] 2) Collect and record user learning data, and judge whether the trigger condition of pre-knowledge point search is met. If yes, execute step 3), if not, execute step 5). User learning data includes the ability value of each knowledge point, knowledge point Number of studies and course progress;

[0055] 3) using the graph search algorithm to search the preceding weak knowledge points of the current knowledge point in the graph database, and obtain the priority learning order of each preceding weak knowledge point;

[0056] 4) push the corresponding learning content based on the priority learning order, and enter the knowledge point review stage;

[0057] 5) Push the corresponding learning content based on the current knowl...

Embodiment 2

[0099] This embodiment provides an adaptive computer learning system based on a graph search algorithm corresponding to Embodiment 1, including:

[0100] a storage module for establishing a knowledge graph and storing the knowledge graph in a graph database;

[0101] The judgment module is used for collecting and recording user learning data, and judging whether the trigger condition of the pre-knowledge point search is met;

[0102] a search module, which responds when the judgment result of the judgment module is yes, and is used to search for the pre-weak knowledge points of the current knowledge point in the graph database by using a graph search algorithm, and obtain the priority learning order of each pre- weak knowledge point;

[0103] a first push module, configured to push corresponding learning content according to the priority learning order;

[0104] The second push module is used to push the corresponding learning content according to the current knowledge point....

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Abstract

The invention relates to a self-adaptive learning method based on a graph search algorithm and a computer learning system, and the method comprises the following steps: 1) building a knowledge graph,and storing the knowledge graph in a graph database; 2) collecting and recording user learning data, judging whether a trigger condition of front knowledge point searching is met or not, if yes, executing the step 3), and if not, executing the step 5); 3) searching front weak knowledge points of the current knowledge points in the graph database by utilizing the graph search algorithm, to obtain apriority learning sequence of the front weak knowledge points; 4) pushing the corresponding learning contents based on the priority learning sequence, and 5) pushing the corresponding learning contents based on the current knowledge point. Compared with the prior art, the method has the advantages of being fast in search, improving the learning efficiency and the like.

Description

technical field [0001] The invention relates to a learning device for online education, in particular to an adaptive learning method based on a graph search algorithm and a computer system. Background technique [0002] With the development of the Internet, education methods are also subtly affected by new technologies. The rapid development and application of artificial intelligence has provided new ideas for the field of online education. In recent years, products that combine artificial intelligence in Internet education have developed very rapidly. Most of these products have proposed the concept of knowledge map. The knowledge map in online intelligent education products is to summarize and subdivide all the knowledge points in the subject area of ​​the students, and mark the front and rear relations of each knowledge point, and use them in a complete manner. represented in the form of a network diagram. The knowledge graph is a complex graph describing the relationsh...

Claims

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Application Information

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IPC IPC(8): G06F16/31G06F16/36G09B5/08
CPCG06F16/316G06F16/367G09B5/08
Inventor 崔炜殷龙
Owner SHANGHAI SQUIRREL CLASSROOM ARTIFICIAL INTELLIGENCE TECH CO LTD
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