@article{ART003212653},
author={Sung-Kwang Song and Hyeon-Jeong Mun and Young-Ji Kim and Yong-Tae Woo},
title={Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2025},
volume={30},
number={6},
pages={21-29}
TY - JOUR
AU - Sung-Kwang Song
AU - Hyeon-Jeong Mun
AU - Young-Ji Kim
AU - Yong-Tae Woo
TI - Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers
JO - Journal of The Korea Society of Computer and Information
PY - 2025
VL - 30
IS - 6
PB - The Korean Society Of Computer And Information
SP - 21
EP - 29
SN - 1598-849X
AB - In this study, we propose the Hi-BERT model to identify effectively and to learn semantic associations between recruitment ontology generated automatically from recruitment information and academic papers using generative AI. The proposed model can learn semantic associations between ontology-transformed sentences, which are structural information of recruitment ontology converted into natural language, and academic papers.
In addition, domain-specific characteristics are learned from recruitment information and academic papers, and optimized by the contrastive learning technique. The proposed model can improve the limitations of knowledge transfer between different domains of existing sentence embedding models such as KLUE and KoSimCSE-BERT. In particular, the learning method utilizing ontology-transformed sentences proposed in this study can provide richer semantic understanding than existing models trained by simple text corpus. In the future, the proposed model is expected to be used as a base model for developing expert search systems.
KW - BERT;Pre-trained Language Model;Ontology;Generative AI;Contrastive Learning
DO -
UR -
ER -
Sung-Kwang Song, Hyeon-Jeong Mun, Young-Ji Kim and Yong-Tae Woo. (2025). Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers. Journal of The Korea Society of Computer and Information, 30(6), 21-29.
Sung-Kwang Song, Hyeon-Jeong Mun, Young-Ji Kim and Yong-Tae Woo. 2025, "Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers", Journal of The Korea Society of Computer and Information, vol.30, no.6 pp.21-29.
Sung-Kwang Song, Hyeon-Jeong Mun, Young-Ji Kim, Yong-Tae Woo "Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers" Journal of The Korea Society of Computer and Information 30.6 pp.21-29 (2025) : 21.
Sung-Kwang Song, Hyeon-Jeong Mun, Young-Ji Kim, Yong-Tae Woo. Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers. 2025; 30(6), 21-29.
Sung-Kwang Song, Hyeon-Jeong Mun, Young-Ji Kim and Yong-Tae Woo. "Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers" Journal of The Korea Society of Computer and Information 30, no.6 (2025) : 21-29.
Sung-Kwang Song; Hyeon-Jeong Mun; Young-Ji Kim; Yong-Tae Woo. Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers. Journal of The Korea Society of Computer and Information, 30(6), 21-29.
Sung-Kwang Song; Hyeon-Jeong Mun; Young-Ji Kim; Yong-Tae Woo. Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers. Journal of The Korea Society of Computer and Information. 2025; 30(6) 21-29.
Sung-Kwang Song, Hyeon-Jeong Mun, Young-Ji Kim, Yong-Tae Woo. Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers. 2025; 30(6), 21-29.
Sung-Kwang Song, Hyeon-Jeong Mun, Young-Ji Kim and Yong-Tae Woo. "Hi-BERT : A Semantic Relation Learning Model for Recruitment Ontology and Academic Papers" Journal of The Korea Society of Computer and Information 30, no.6 (2025) : 21-29.
