Journal of Computer Technology and Software

Vol. 2 No. 1 (2024)
Articles

Overview of Entity-Relationship Extraction Zizi Zhang , Michael Smith

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  • Zizi Zhang,
  • Michael Smith

Published 2024-04-28

Keywords

  • Natural language processing; Entity relationship extraction; Deep learning

How to Cite

Zhang, Z., & Smith, M. (2024). Overview of Entity-Relationship Extraction Zizi Zhang , Michael Smith. Journal of Computer Technology and Software, 2(1), 14–16. Retrieved from https://ashpress.org/index.php/jcts/article/view/26
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Information extraction is a pivotal focus in the field of natural language processing, with entity-relationship extraction being a key component. This paper examines the historical development of entity-relationship extraction and discusses the characteristics of various entity-relationship extraction methods. Additionally, it presents an overview of several leading entity-relationship extraction techniques currently in use. The paper concludes with a forward-looking perspective on the future of entity-relationship extraction, particularly in the context of advancements in deep learning.

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