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국내 기록관리학 연구동향 분석을 위한 토픽모델링 기법 비교 - LDA와 HDP를 중심으로 -

Comparison of Topic Modeling Methods for Analyzing Research Trends of Archives Management in Korea: focused on LDA and HDP

  • 박준형 (전북대학교 일반대학원 기록관리학과) ;
  • 오효정 (전북대학교 기록관리학과, 문화융복합 아카이빙연구소)
  • 투고 : 2017.11.16
  • 심사 : 2017.12.16
  • 발행 : 2017.12.30

초록

본 연구에서는 최근 각광을 받고 있는 텍스트마이닝 기법인 LDA 토픽모델링과 이를 변형한 HDP 토픽모델링을 적용하여 국내 기록관리학의 연구동향을 분석하고자 한다. 이를 위해 국내 기록관리학 관련 학술지 2종과 문헌정보학 관련 학술지 4종에서 1997년부터 2016년까지 발표된 기록관리학 관련 논문 1,027건을 수집하고 적절한 전처리과정을 거친 후 LDA 토픽모델링과 HDP 토픽모델링을 각각 수행하였다. 또한 토픽모델링 시각화 도구인 LDAvis를 활용하여 토픽별 거리를 가시적으로 표현하고 세부 대표 키워드를 분석하였다. 두 토픽모델링을 비교한 결과, LDA 토픽모델링은 전반적으로 해당 도메인을 대표하는 주요 키워드로 빈도수에 영향을 많이 받았으며, HDP 토픽모델링은 각 토픽별 특징을 파악할 수 있는 특수한 키워드가 많이 도출되었다. 이를 통해 LDA는 국내 기록관리학 내에 거시적으로 대표되는 주제들을, HDP는 세부 주제별 미시적인 핵심 키워드를 도출하는데 효과적임을 알 수 있었다.

The purpose of this study is to analyze research trends of archives management in Korea by comparing LDA (Latent Semantic Allocation) topic modeling, which is the most famous method in text mining, and HDP (Hierarchical Dirichlet Process) topic modeling, which is developed LDA topic modeling. Firstly we collected 1,027 articles related to archives management from 1997 to 2016 in two journals related with archives management and four journals related with library and information science in Korea and performed several preprocessing steps. And then we conducted LDA and HDP topic modelings. For a more in-depth comparison analysis, we utilized LDAvis as a topic modeling visualization tool. At the results, LDA topic modeling was influenced by frequently keywords in all topics, whereas, HDP topic modeling showed specific keywords to easily identify the characteristics of each topic.

키워드

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피인용 문헌

  1. 텍스트마이닝 기법을 활용한 미국산업응용수학 학회지의 연구 현황 및 동향 분석 vol.20, pp.7, 2017, https://doi.org/10.5392/jkca.2020.20.07.212
  2. 토픽 모델링 기반의 국내외 공공데이터 연구 동향 비교 분석 vol.19, pp.2, 2017, https://doi.org/10.14400/jdc.2021.19.2.001
  3. 토픽 모델링을 이용한 지속가능패션 연구 동향 분석 vol.29, pp.4, 2017, https://doi.org/10.29049/rjcc.2021.29.4.538