본 연구는 전자파 인체영향 연구논문 데이터베이스의 활용성과 객관성을 높이기 위한 연구형태 자동분류 기법을 제안한다. 제안하는 기법은 문서 임베딩(embedding) 모델인 Doc2Vec을 사용하여 연구논문의 텍스트 데이터를 벡터로 표현하고, 동물실험, 세포실험, 역학조사에 해당하는지 판단하는 3가지 연구형태 이진분류기를 학습시켜, 전자파 인체영향연구논문의 연구형태를 자동으로 분류한다. 제안하는 기법의 성능을 검증하기 위하여 전자파 인체영향 관련 연구논문120개 중 90개를 학습 세트로, 30개를 테스트 세트로 하여 제안하는 기법을 실험하였다. 그 결과, 제안하는 기법이 평균88 %의 높은 정확도로 전자파 인체영향 연구논문의 연구형태를 분류하는 것을 확인할 수 있었다.
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