Design and Implementation of Curriculum System Based on Knowledge Graph
Xiaobing Yu, Mike Stahr, Han Chen, and Runming Yan

TL;DR
This paper presents a method to visualize and analyze university curriculum systems using a knowledge graph based on Google Knowledge Graph and Neo4j, facilitating better course arrangement and understanding of course relationships.
Contribution
It introduces a novel approach to construct and visualize university curriculum knowledge graphs using Neo4j, enhancing course analysis and planning.
Findings
Effective visualization of course relationships
Improved analysis of course prerequisites
Facilitated quick querying of course information
Abstract
With the fact that the knowledge in each field in university is keeping increasing, the number of university courses is becoming larger, and the content and curriculum system is becoming much more complicated than it used to be, which bring many inconveniences to the course arrangement and analysis. In this paper, we aim to construct a method to visualize all courses based on Google Knowledge Graph. By analysing the properties of the courses and their preceding requirements, we want to extract the relationship between the precursors and the successors, so as to build the knowledge graph of the curriculum system. Using the graph database Neo4j [7] as the core aspect for data storage and display for our new curriculum system will be our approach to implement our knowledge graph. Based on this graph, the venation relationship between courses can be clearly analysed, and some difficult…
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Taxonomy
TopicsAdvanced Graph Neural Networks · Recommender Systems and Techniques · Biomedical Text Mining and Ontologies
