소프트웨어 분야 취업 결정 요인에 대한 XAI 모델 적용 연구 : 일반대학교와 전문대학 졸업자를 중심으로
Application of XAI Models to Determine Employment Factors in the Software Field : with focus on University and Vocational College Graduates
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
The purpose of this study is to explain employment factors in the software field. For it, the Graduates Occupational Mobility Survey by the Korea employment information service is used. This paper proposes employment models in the software field using machine learning. Then, it explains employment factors of the models using explainable artificial intelligence. The models focus on both university graduates and vocational college graduates. Our works explain and interpret both black box model and glass box model. The SHAP and EBM explanation are used to interpret black box model and glass box model, respectively. The results describes that positive employment impact factors are major, vocational education and training, employment preparation setting semester, and intern experience in the employment models. This study provides a job preparation guide to universitiy and vocational college students that want to work in software field.
Abstract
The purpose of this study is to explain employment factors in the software field. For it, the Graduates Occupational Mobility Survey by the Korea employment information service is used. This paper proposes employment models in the software field using machine learning. Then, it explains employment factors of the models using explainable artificial intelligence. The models focus on both university graduates and vocational college graduates. Our works explain and interpret both black box model and glass box model. The SHAP and EBM explanation are used to interpret black box model and glass box model, respectively. The results describes that positive employment impact factors are major, vocational education and training, employment preparation setting semester, and intern experience in the employment models. This study provides a job preparation guide to universitiy and vocational college students that want to work in software field.
참고문헌 (16)
- 황정원, "청년고용정책이 대졸 청년층 취업에 미치는 효과 분석", 직업능력개발연구, 24(2), pp.67~94 (2021)
- 김효정, "데이터마이닝을 이용한 대학생들의 취업 로드맵에 관한 기초 연구", 디지털산업정보학회 논문지, 19(1), pp.129~138 (2023)
- 권준희, "부스팅 기계 학습과 SHAP를 이용한 설명 가능한 소프트웨어 분야 대졸자 취업 모델 개발", 디지털산업정보학회 논문지, 19(3), pp.177~192 (2023)
- 송선혜, "대학 취업률 경로 분류와 취업률 결정 요인-대학 진로·취업 지원 현황을 중심으로", 직업능력개발연구, 23(2), pp.114~138 (2020)
- 최재식, "설명가능 인공지능 연구동향", 정보과학회지, 37(7), pp.8~14 (2019)
- Alejandro Barredo Arrieta, "Explainable Artificial Intelligence(XAI) : Concepts, Taxonomies, Opp ortunities and Challenges toward Responsible AI", Information Fusion, 58, pp.82~115 (2020)
- Arun Rai, "Explainable AI : From black box to glass box", Journal of the Academy of Marketing Science, 48, pp.137~141 (2020)
- Pantelis Linardatos, "Explainable AI: A Review of Machine Learning Interpretability Methods", Entropy, 23(1) (2021)
- Scott M. Lundberg, "A Unified Approach to Interpreting Model Predictions", Proceedings of the 31st International Conference on Neural Information Processing Systems, pp.4768~4777 (2017)
- 김홍비, "악성 사이트 탐지를 위한 설명가능한 인공지능(XAI) 기반 기계학습 특징 선별에 관한 연구", 2022년도 한국통신학회 추계종합학술발표회 논문집, pp.411~412 (2022)
- "대졸자직업이동경로조사(GOMS)" (2024), 한국고용정보원[URL]
- 문찬주, "대학생의 취업준비 시작 시기에 따른 학업성취 및 노동시장 이행 성과 분석", 교육재정연구, 27(3), pp.27~56 (2018)
- 김민선, "전문대학 졸업자의 첫 직장 취업성과에 대한 영향요인 분석", 지방교육경영, 26(3), pp.29~54 (2023)
- 김희준, "PSM기반 대졸취업자의 전공관련 취업 결정 요인에 관한 연구", 한국자료분석학회, 21(4), pp.1827~1839 (2019), 한국자료분석학회
- "What the FAQ" (2024)[URL]