计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 573-578.doi: 10.11896/jsjkx.191200141

• 交叉&应用 • 上一篇    下一篇

数学课程知识图谱构建及其推理

张春霞, 彭成, 罗妹秋, 牛振东   

  1. 北京理工大学计算机学院 北京 100081
  • 出版日期:2020-11-15 发布日期:2020-11-17
  • 通讯作者: 张春霞(cxzhang@bit.edu.cn)。
  • 基金资助:
    北京理工大学科技创新计划(GZ2019075102);北京理工大学教育教学改革项目(068)

Construction of Mathematics Course Knowledge Graph and Its Reasoning

ZHANG Chun-xia, PENG Cheng, LUO Mei-qiu, NIU Zhen-dong   

  1. School of Computer Science and Technology,Beijing Institute of Technology,Beijing 100081,China
  • Online:2020-11-15 Published:2020-11-17
  • About author:ZHANG Chun-xia,born in 1974,Ph.D,associate professor.Her main research interests include big data search and mining,and knowledge graph construction,etc.
  • Supported by:
    This work was supported by the Science and Technology Innovation Plan of Beijing University of Technology (GZ2019075102) and Education and Teaching Reform Project of Beijing University of Technology(068).

摘要: 课程知识图谱构建已成为知识图谱、网络学习和知识服务等领域的重要研究内容。以数学类课程为研究对象,构建了数学课程本体,设计了基于数学课程本体的数学课程知识图谱构建方法,提出了基于数学课程知识图谱的知识推理方法。数学课程本体的特点是:数学课程本体包括数学课程上层本体、数学课程内容本体以及数学课程习题本体。数学课程上层本体描述不同数学课程共享的概念化知识,数学课程内容本体描述特定课程的知识,数学课程习题本体描述数学课程习题的内涵和性质。数学课程知识图谱的特点是:基本模型和扩展模型的分层融合性,概念的正实例和负实例的引入,以及与数学课程内容本体的有机衔接。基于数学课程知识图谱的知识推理方法的特色是:构建了推理类型分类体系,该分类体系从本体角度给出了推理知识的类型和在数学课程知识图谱中的定位和关联关系。离散数学课程实验,表明了知识图谱构建和推理方法的有效性。数学课程知识图谱及其推理为用户提供了一种形式化的、显式的课程知识表示、知识组织和知识推理模型,从而改善了知识服务效果。

关键词: 数学课程内容本体, 数学课程上层本体, 数学课程知识图谱, 知识推理

Abstract: The construction of course knowledge graph has become an important research content in the fields of knowledge graph,E-learning and knowledge service and so on.This paper takes mathematics courses as the research object,constructsmathe-matics course ontology (MCO),designs a method of building mathematics course knowledge graph (MCKG) in terms of mathematics course ontology,and proposes an approach of knowledge reasoning founded on MCKG.The characteristics of MCO are that it includes mathematics course top-level ontology,mathematics course content ontology,and mathematics course exercise ontology.Mathematics course top-level ontology is to depict shared conceptualizing knowledge of different mathematics courses.Mathematics course content ontology is to describe knowledge of specific courses,while mathematics course exercise ontology is to depict intensions and properties of exercises of mathematics courses.The traits of MCKG are that hierarchical fusion of basic model and extended model,introduction of positive instances and negative instances of concepts,and organic integration with mathematics course content ontology.The characteristic of knowledge inference based on MCKG is that the taxonomy of infe-rence types is built.This taxonomy gives types of inference knowledge,and location and associated relationships in MCKG from the point view of ontology.The experiments about the discrete mathematics course show the validity of the proposed knowledge graph construction and reasoning methods.The mathematics course knowledge graph and its reasoning provide a formal explicit model of course knowledge representation,organization,and reasoning for users,and can improve knowledge service effects.

Key words: Knowledge graph of mathematics course, Knowledge reasoning, Mathematics course content ontology, Mathematics course top-level ontology

中图分类号: 

  • TP391
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