양방향 인재매칭을 위한 BERT 기반의 전이학습 모델A BERT-based Transfer Learning Model for Bidirectional HR Matching
- Other Titles
- A BERT-based Transfer Learning Model for Bidirectional HR Matching
- Authors
- 오소진; 장문경; 송희석
- Issue Date
- Aug-2021
- Publisher
- 한국데이터전략학회
- Keywords
- HR Matching; Job Recommendation; BERT; Transfer Learning; Pre-trained Language Model; Fine-tuning Deep Learning Model
- Citation
- Journal of Information Technology Applications & Management, v.28, no.4, pp.33 - 43
- Journal Title
- Journal of Information Technology Applications & Management
- Volume
- 28
- Number
- 4
- Start Page
- 33
- End Page
- 43
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/84663
- ISSN
- 1598-6284
- Abstract
- While youth unemployment has recorded the lowest level since the global COVID-19 pandemic, SMEs(small and medium sized enterprises) are still struggling to fill vacancies. It is difficult for SMEs to find good candidates as well as for job seekers to find appropriate job offers due to information mismatch. To overcome information mismatch, this study proposes the fine-turning model for bidirectional HR matching based on a pre-learning language model called BERT(Bidirectional Encoder Representations from Transformers). The proposed model is capable to recommend job openings suitable for the applicant, or applicants appropriate for the job through sufficient pre-learning of terms including technical jargons. The results of the experiment demonstrate the superior performance of our model in terms of precision, recall, and f1-score compared to the existing content-based metric learning model. This study provides insights for developing practical models for job recommendations and offers suggestions for future research.
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