A subject map conflict detection method and system based on knowledge association

Abstract

The invention belongs to the field of educational technology and discloses a subject map conflict detection method and system based on knowledge association. The method comprises the following steps of calculating the correlation Rk between knowledge elements in the subject map based on a method of calculating the correlation relation of knowledge elements based on the path and depth; calculatingthe relativity Rr between the resource groups (including knowledge elements) associated with the knowledge elements in the topic map, and calculating the similarity between the knowledge elements withthe resource description information associated with the knowledge elements; calculating the deviation consistency between Rk and Rr, and calculating the degree of deviation consistency between Rk and Rr by calculating the correlation between knowledge elements based on path and depth and by calculating the correlation between Rk and Rr by using the word vector constructed by the multi-dimensional description information tag of resource group. The invention helps to enhance the correlation of the knowledge structure combing and the resources associated with the knowledge, and helps learners to better and faster construct the personalized knowledge system.

Description

technical field [0001] The invention belongs to the field of education technology, and in particular relates to a method and system for detecting conflicts of theme graphs based on knowledge association. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: [0003] Topic map is one of the effective methods for knowledge aggregation, and its biggest advantage is that it can give full play to the customization of knowledge composition and knowledge scope by topic builders. In this way, learners have a strong correlation with the knowledge structure combing and the resources associated with knowledge during the learning process, which helps learners quickly build a personalized knowledge system. However, it is unreasonable to construct a knowledge system that is limited to the depth and cognitive breadth of the learner. In this situation, there will be two situations. One is that the name and logo of the tuple are cr...

AI Technical Summary

Problems solved by technology

[0007] (1) Because the name and logo of the tuple are customized by the builder, there may be a deviation from the definition;

[0008] (2) The associated knowledge elements under the tuple are individually associated to the wrong range, which may cause inconsistencies among all the associated knowledge elements under this knowledge element group, and there may be a majority of knowledge elements and a small number of knowledge elements. The scope of the represented knowledge is not under the description scope of the same knowledge tuple;

[0009] Therefore, the topic map constructed by learners may be unreasonable, and it is easy to cause inconsistency in the range of knowledge domains represented by the topic map

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