Mining prerequisite relations among learning objects

Kexin MA; Bifan WEI; Jie MA; Jun LIU; Yi HUANG; Min HU; Junlan FENG

doi:10.11959/j.issn.2096-0271.2020052

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Mining prerequisite relations among learning objects

TOPIC：EDUCATIONAL BIG DATA | 更新时间：2024-06-03

- Mining prerequisite relations among learning objects
- Big Data Research Vol. 6, Issue 6, Pages: 2020052-1(2020)
- 作者机构：
  
  1. 西安交通大学计算机科学与技术学院，陕西西安 710049
  2. 陕西省天地网技术重点实验室，陕西西安 710049
  3. 中国移动研究院，北京 100032
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2020052
  CLC： TP391.1
- Online First：2020-11，
  
  Published：15 November 2020
- 稿件说明：
移动端阅览
Kexin MA, Bifan WEI, Jie MA, et al. Mining prerequisite relations among learning objects[J]. Big Data Research, 2020, 6(6): 2020052-1.
DOI：

Kexin MA, Bifan WEI, Jie MA, et al. Mining prerequisite relations among learning objects[J]. Big Data Research, 2020, 6(6): 2020052-1. DOI： 10.11959/j.issn.2096-0271.2020052.

摘要

先序关系指知识主题之间学习的先后依赖关系。已有的先序关系挖掘方法大多是流线型的方式，易导致错误累计，且严重依赖可能导致错误先序关系的超链接。为了解决以上问题，先对知识主题间的先序关系进行统计分析，发现了先序关系的不对称性特征；接着提出从文本中挖掘知识主题间的先序关系的端到端先序关系挖掘模型。该模型基于文本中抽取出的术语间上下位关系，计算知识主题的相关术语集间先序关系的不对称性，进而预测知识主题间的先序关系。实验结果表明，该方法具有较优的先序关系抽取性能。

Abstract

Prerequisite relation refers to the learning dependency between learning objects.Most previous works mined prerequisite relations in a pipelined way and heavily relied on hyperlinks

which lead to the accumulation of errors.To address these issues

prerequisite relations among knowledge topics were analyzed

and the asymmetry feature of prerequisite relation was found out.An end-to-end prerequisite relation model for mining prerequisite relations from texts was proposed.Based on the hyponymy relations between terms extracted from texts

this model calculates the asymmetry of prerequisite relation among related terms of learning objects

and then predicts the prerequisite relation betweens learning objects.The experimental results show that the proposed method achieves the state-of-the-art performance.

关键词

Keywords

references

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