计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 573-578.doi: 10.11896/jsjkx.191200141
张春霞, 彭成, 罗妹秋, 牛振东
ZHANG Chun-xia, PENG Cheng, LUO Mei-qiu, NIU Zhen-dong
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。
中图分类号:
[1] Knowledge Graph [EB/OL].https://en.wikipedia.org/wiki/Knowledge_Graph. [2] 中文知识图谱[EB/OL].https://baike.baidu.com/item/%E4%B8%AD%E6%96%87%E7%9F%A5%E8%AF%86%E5%9B%BE%E8%B0%B1. [3] 2018知识图谱发展报告[EB/OL].https://www.useit.com.cn/thread-20216-1-1.html. [4] WU X.From Big Data to Big Knowledge:HACE+BigKE[J].Journal of Computer Science,2016,43(7):3-6. [5] XIONG F,GAO J.Entity Alignment for Cross-Lingual Know-ledge Graph with Graph Convolutional Networks[C]//The 28th International Joint Conference on Artificial Intelligence.2019:6480-6481. [6] WANG X,WANG D,XU C,et al.Explainable Reasoning over Knowledge Graphs for Recommendation[C]//The AAAI Conference on Artificial Intelligence.2019:5329-5336. [7] LI T,WANG C,LI H.Development and Construction of Know-ledge Graph [J].Journal of Nanjing University of Science and Technology,2017,41(1):22-34. [8] ZHU M,PAO B,XU C.Research Progress on Development and Construction of Knowledge Graph[J].Journal of Nanjing University of Information Science and Technology(Natural Science Edition),2017,9(6):575-582. [9] LIU Q,LI Y,DUAN H,et al.Knowledge Graph ConstructionTechniques [J].Journal of Computer Research and Development,2016,53(3):582-600. [10] GUAN S,JIN X,JIA Y,et al.Knowledge Reasoning OverKnowledge Graph:A Survey[J].Journal of Software,2018,29(10):2966-2994. [11] ZHANG M.Research on Construction of Course KnowledgeGraph and Search Technology [D].Wuhan:Wuhan University,2016. [12] LIU Z,LI Z.Research on Information Theory Teaching Reform Based on Knowledge Graph Theory[J].Computer Knowledge and Technology,2018,14(12):125-127. [13] XIE Z,LIU Y.Research on Teaching Reform of Digital Media Knowledge by Means of Knowledge Graph Modeling[J].Software Guild,2017,16(11):230-232. [14] WANG L.Reconstruction of MOOC Courses based on Multimodal Knowledge Map from the Perspective of Deep Learning [J].Modern Education Technology,2018,28(10):100-106. [15] ZHONG Y.Ontology-based Curriculum Knowledge Point Mo-deling of Major of Information Management and Information System [J].Information Research,2013(8):94-98. [16] ZENG Q,CAO C,SUI Y,et al.Research on Ontology-basedMathematical Knowledge Acquisition and Knowledge Heritance Mechanism [J].Microelectronics & Computer,2003,20(9):19-27. [17] HE Z,ZHUANG Y.Discrete Mathematics Course Autonomous Learning System Based on Concept Map [J].Higher Education of Sciences,2018(1):90-95. [18] LI H,YANG G.Course Development of e-Learning based on Ontology [J].Computer Engineering and Design,2010,31(4):881-884. [19] JIANG Y.Construction and Application of Ontology-basedMathematics Knowledge Base [D].Chengdu:University of Electronic Science and Technology of China,2011. [20] LV J,YU X.Ontology Modeling and Reasoning for Curriculum Knowledge[J].Computer Engineering,2011,37(4):61-63. [21] GRUBER T R.Toward Principles for the Design of Ontologies Used for Knowledge Sharing?[J].International Journal of Human-Computer Studies,1995,43(5/6):907-928. [22] MIAO Z.Research on Technologies for Building Ontology Semi-Automatically [J].Journal of PLA University of Science and Technology,2006,7(5):426-431. [23] QU W,GENG S,ZHANG L.Discrete Mathematics [M].Beijing:Beijing Higher Education Press,2017. [24] Apache Jena[EB/OL].http://jena.apache.org/ .[2018]. [25] 数学课程特性[EB/OL].https://baike.baidu.com/item/%E6%95%B0%E5%AD%A6%E8%AF%BE%E7%A8%8B%E7%89%B9%E6%80%A7/19145562. [26] 浅谈数学的特点[EB/OL].https://www.xzbu.com/9/view-4180391.htm. |
[1] | 马瑞新, 李泽阳, 陈志奎, 赵亮. 知识图谱推理研究综述 Review of Reasoning on Knowledge Graph 计算机科学, 2022, 49(6A): 74-85. https://doi.org/10.11896/jsjkx.210100122 |
[2] | 杨如涵, 戴毅茹, 王坚, 董津. 基于表示学习的工业领域人机物本体融合 Humans-Cyber-Physical Ontology Fusion of Industry Based on Representation Learning 计算机科学, 2021, 48(5): 190-196. https://doi.org/10.11896/jsjkx.200500023 |
[3] | 杭婷婷, 冯钧, 陆佳民. 知识图谱构建技术:分类、调查和未来方向 Knowledge Graph Construction Techniques:Taxonomy,Survey and Future Directions 计算机科学, 2021, 48(2): 175-189. https://doi.org/10.11896/jsjkx.200700010 |
[4] | 文习明,方良达,余泉,常亮,王驹. 多智能体模态逻辑系统KD45n中的知识遗忘 Knowledge Forgetting in Multi-agent Modal Logic System KD45n 计算机科学, 2019, 46(7): 195-205. https://doi.org/10.11896/j.issn.1002-137X.2019.07.030 |
[5] | 李智星, 任诗雅, 王化明, 沈柯. 基于非结构化文本增强关联规则的知识推理方法 Knowledge Reasoning Method Based on Unstructured Text-enhanced Association Rules 计算机科学, 2019, 46(11): 209-215. https://doi.org/10.11896/jsjkx.181001939 |
[6] | 徐凤生,于秀清,史开泉. 动态知识智能发现与属性逻辑动态关系 Intelligent Discovery of Dynamic Knowledges and Logic Dynamic Relation between their Attributes 计算机科学, 2015, 42(4): 160-165. https://doi.org/10.11896/j.issn.1002-137X.2015.04.032 |
[7] | 邹丽,谭雪微,张云霞. 语言真值直觉模糊逻辑的知识推理 Knowledge Reasoning Based on Linguistic Truth-valued Intuitionstic Fuzzy Logic 计算机科学, 2014, 41(1): 134-137. |
[8] | 张敬谊,童庆,肖筱华. 用于应急指挥的知识推理技术研究 Research on Knowledge Reasoning Technology in Emergency Command System 计算机科学, 2013, 40(2): 261-264. |
[9] | 倪俊,陈晓苏,刘辉宇,李劲. 网络安全策略求精一致性检测和冲突消解机制的研究 Research on Network Security Policy Refinement Consistency of Detection and Conflict Resolution Mechanisms 计算机科学, 2011, 38(2): 32-37. |
[10] | 游福成 苏占东 谢永红 杨炳儒. 多智体在IDSSIM结构设计中的应用 计算机科学, 2004, 31(3): 118-120. |
[11] | 江莉 刘三阳 王珏 陆爱国. Vague决策表的知识获取 计算机科学, 2004, 31(2): 111-112. |
[12] | 王洁 鞠实儿. 概率逻辑程序 计算机科学, 2003, 30(7): 1-3. |
[13] | 黄智生. 关于知识的推理新进展 计算机科学, 1994, 21(3): 49-52. |
|