Person-relation extraction using bert based knowledge graph
- Authors
- Yang S.M.; Yoo S.Y.; Ahn Y.S.; Jeong O.R.
- Issue Date
- Jun-2020
- Publisher
- ICIC International
- Keywords
- Knowledge graph; Named entity recognition; Relation extraction
- Citation
- ICIC Express Letters, Part B: Applications, v.11, no.6, pp.539 - 544
- Journal Title
- ICIC Express Letters, Part B: Applications
- Volume
- 11
- Number
- 6
- Start Page
- 539
- End Page
- 544
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/52281
- DOI
- 10.24507/icicelb.11.06.539
- ISSN
- 2185-2766
- Abstract
- Artificial intelligence technology has been actively researched in the areas of image processing and natural language processing. Recently, with the release of Google’s language model BERT, the importance of artificial intelligence models has attracted attention in the field of natural language processing. In this paper, we propose a knowledge graph to build a model that can extract people in a document using BERT, and to grasp the relationship between people based on the model. In addition, to verify the applicability of person extraction techniques using BERT based knowledge graphs, we conduct a performance comparison experiment with other person extraction models and apply our proposed method to the case study. © 2020, ICIC International.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - IT융합대학 > 소프트웨어학과 > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.