Method for quantitatively calculating association degree among multi-tab learning resources

Abstract

The invention discloses a method for quantitatively calculating an association degree among multi-tab learning resources. The method comprises the following steps: 1) building a learning resource semantic model; 2) assessing the similarity and relevance among learning resources; and 3) calculating the similarity and relevance among the multi-tab learning resources. According to the method, the structural features of the learning resources are indexed by analysis of a plurality of knowledge points, and the similarity is calculated according to a coincidence degree among same knowledge points included in the learning resources. The relevance is calculated according to properties such as semantics and structures among different and similar knowledge points, so that a method for quantitatively assessing and calculating the association degree among the learning resources is formed, and a research basis is laid for association analysis and association retrieval of the learning resources.

Description

technical field [0001] The invention relates to the technical field of concrete bridge decks, in particular to a method for quantitatively calculating the correlation degree of multi-label learning resources. Background technique [0002] The invention belongs to a method for evaluation and quantitative calculation of correlation degree, and the patent mainly relates to learning resources for multi-knowledge point indexing and knowledge ontology in the field of education. Using methods such as resource association, similarity evaluation, and correlation evaluation, different types of resources in the field of education, such as teaching materials, exercise sets, test questions, test papers, teaching videos, recordings, etc., are marked with knowledge points, and by analyzing multiple knowledge points Citing the structural characteristics of learning resources, the similarity is calculated from the overlap of the same knowledge points between learning resources; the correlati...

AI Technical Summary

Problems solved by technology

[0003] With the wide application of IT technology in the field of education and teaching, various types of digital teaching resources have accumulated on the Internet, such as test questions, test papers, recordings, animations, teaching videos, courseware, etc., forming various educational and teaching resources of different sizes. resource library, but the existing technology has not realized the efficient integration and interrelationship of these resources, and the existing research mainly focuses on the similarity or correlation of ontology concepts, words, and texts. Calculation methods are relatively scarce

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