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Construction and Teaching Application of Knowledge Graph in the Field of International Trade

Published: 18 November 2024 Publication History

Abstract

This study aims to explore the construction of knowledge graphs in the field of international trade and its effect in teaching applications. By in-depth analysis of the core entities and relationships of international trade, this paper successfully constructs an extensive international trade knowledge graph that integrates information from multiple data sources and provides a novel perspective to understand the complexity of international trade. Furthermore, the research shows how teaching methods based on knowledge graphs can significantly improve students' learning engagement, knowledge mastery, and practical abilities. Through pre- and post-test comparison, student feedback and teaching case analysis, it is proved that knowledge graph can be used as an effective teaching tool to promote students' in-depth understanding and application of international trade concepts. Despite some limitations in data sources and teaching implementation, this study provides valuable insights and suggestions for future research and teaching practice in this area.

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Zhong, L., Wu, J., Li, Q., Peng, H., Wu, X.: A Comprehensive Survey on Automatic Knowledge Graph Construction. ACM Computing Surveys 56, 1 - 62 (2023). Link
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Chen, P., Lu, Y., Zheng, V., Chen, X., Yang, B.: KnowEdu: A System to Construct Knowledge Graph for Education. IEEE Access 6, 31553-31563 (2018). Link
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Rospocher, M., Erp, M.V., Vossen, P., Fokkens, A., Aldabe, I., Rigau, G., Etxabe, A.S., Ploeger, T., Bogaard, T.: Building event-centric knowledge graphs from news. J. Web Semant. 37-38, 132-151 (2016). Link
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ICDSM '24: Proceedings of the International Conference on Decision Science & Management
April 2024
356 pages
ISBN:9798400718151
DOI:10.1145/3686081
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 November 2024

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Author Tags

  1. Data integration
  2. International trade
  3. Knowledge graph
  4. Teaching application

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