Knowledge graph personalized learning path recommendation method based on RankNet-transformer

A knowledge map and learning path technology, applied in character and pattern recognition, unstructured text data retrieval, instruments, etc., can solve the problems of inaccuracy and low learning efficiency of learners, and achieve the effect of improving learning efficiency

Pending Publication Date: 2021-08-10
SHANGHAI INST OF TECH
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AI Technical Summary

Problems solved by technology

[0010] Aiming at the inaccuracy of current artificial intelligence learning recommendation, which leads to low learning efficiency of learners, this invention proposes a personalized learning path recommendation method based on RankNet-transformer knowledge map

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  • Knowledge graph personalized learning path recommendation method based on RankNet-transformer
  • Knowledge graph personalized learning path recommendation method based on RankNet-transformer
  • Knowledge graph personalized learning path recommendation method based on RankNet-transformer

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Embodiment Construction

[0039] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings. It should be noted here that the descriptions of these embodiments are used to help understand the present invention, but are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not constitute a conflict with each other.

[0040] like figure 1 As shown, a RankNet-transformer-based personalized learning path recommendation method for knowledge graphs includes the following steps:

[0041] S1, crawl course resources, use HanLP word segmentation algorithm to extract knowledge points, design knowledge point relationship, use adjusted cosine similarity method to calculate the correlation between knowledge points, so as to construct course knowledge point map;

[0042] Since the existing open-...

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Abstract

The invention discloses a knowledge graph personalized learning path recommendation method based on RankNet-transfer. The method comprises the steps of knowledge model construction and model recommendation. In the knowledge model construction, a blind area knowledge point graph is constructed according to the construction of a course knowledge point graph and the analysis result of the knowledge test by the cognitive model. In the recommendation model, a RankNet algorithm and a Transform algorithm are used to realize reordering of blind area knowledge points, and then a topological ordering method is used to traverse a reordering sequence and a blind area knowledge point graph to generate a final knowledge point recommendation sequence. The accuracy of the recommendation result is improved, and the method adapts to the cognitive sequence of the learner.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence learning, and in particular relates to a method for recommending a personalized learning path based on a RankNet-transformer knowledge map. Background technique [0002] In the context of education informatization, a large number of digital learning platforms such as learning websites and teaching software have sprung up, providing learners with massive learning resources, richer learning content, and more flexible learning methods. However, most online learning platforms only simply classify the learning resources on the platform and provide learners with retrieval functions, while learners are less efficient when selecting the retrieved learning resources. At the same time, some online learning platforms only present learning resources to students in a stacked manner according to the age or grade of the learner, without considering the knowledge status, cognitive level, and learn...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/36G06F16/9535G06K9/62
CPCG06F16/367G06F16/9535G06F18/214
Inventor 张媛媛刘云翔
Owner SHANGHAI INST OF TECH
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