基于语义网络的《传感器原理与应用》课程知识图谱构建
Construction of a Knowledge Graph for the Course Principles and Applications of Sensors Based on Semantic Networks
摘要: 随着信息技术的飞速发展和新能源概念的提出，传感器技术作为信息技术的重要组成部分，具有将物理世界的各种信息转换为可处理、可传输的数字信号的能力，是工业自动化、智能家居、环境监测、医疗健康等多个领域不可或缺的关键技术。当前传感器原理与应用人才的培养面临着诸多挑战，如课程内容繁杂、知识点分散、理论与实践脱节等，而我国对传感器原理与应用人才的需求日益迫切。《传感器原理与应用》课程作为电子信息技术类专业的核心课程，其教学质量和学习效率的提升显得尤为重要。知识图谱作为一种有效的知识表示和推理工具，能够帮助学生更好地理解和掌握课程知识点及其之间的关联关系，进而提高学习效率和深度理解能力。主要应用python与neo4j的技术，首先通过数据的规整处理，整合出基本的实体数据表与实体间关系的数据表，再调用数据表中数据组成知识图谱。同时调用生成知识图谱设计了一个基于语义网络的知识图谱问答系统，其主要功能包括数据可视化、搜索知识的问答。本课题旨在设计并实现一个基于语义网络的《传感器原理与应用》课程知识图谱，以期为该课程的教学提供新的辅助手段和学习资源。
Abstract: With the rapid advancement of information technology and the rise of the new energy concept, sensor technology stands out as a vital component of information technology. It boasts the capability to convert diverse information from the physical world into processable and transmittable digital signals. Consequently, sensor technology is indispensable in numerous fields, including industrial automation, smart homes, environmental monitoring, and healthcare. Currently, the cultivation of talents in sensor principles and applications is facing numerous challenges, including cumbersome course content, dispersed knowledge points, and disconnection between theory and practice. Meanwhile, China’s demand for talents in sensor principles and applications is increasingly urgent. The Principles and Applications of Sensors course, as a core course in electronic information technology majors, is particularly important for improving teaching quality and learning efficiency. As an effective tool for knowledge representation and reasoning, knowledge graphs can help students better understand and grasp course knowledge points and their interrelationships, thereby enhancing learning efficiency and in-depth comprehension abilities. Python and Neo4j technologies are mainly applied. Initially, through data regularization processing, basic entity data tables and relationship data tables between entities are integrated. Its main functions include data visualization and question-answering for knowledge search. This project aims to design and implement a semantic network-based knowledge graph for the Principles and Applications of Sensors course, with the anticipation of providing novel auxiliary means and learning resources for the teaching of this course.
文章引用：张英豪, 范小娇, 余方计, 王艳辉, 申雨泽. 基于语义网络的《传感器原理与应用》课程知识图谱构建[J]. 交叉科学快报, 2025, 9(4): 573-581. https://doi.org/10.12677/isl.2025.94072

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