• 한국도서관정보학회지
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• 제50권4호
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• pp.339-358
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• 2019

본 연구의 목적은 광의의 측면에서 지식정보제공이라는 공동의 임무를 수행하는 도서관, 기록관, 박물관간의 협력 플랫폼 구축에 관한 연구의 동향을 토픽 모델링을 통하여 파악하기 위한 것이다. 연구의 목적을 달성하기 위하여 Scopus로부터 이들 세 기관을 동시에 다루는 논문 637편의 서지정보를 수집하였다. 수집된 서지정보 중에서 초록을 대상으로 NetMiner V.4를 통하여 총 5,218개의 단어를 추출한 후 토픽모델링 분석하였으며, 그 결과는 다음과 같다. 첫째, tf-idf의 가중치에 따른 단어출현 빈도를 분석한 결과 '보존(Preservation)'이 가장 높게 나타났으며, 둘째, LDA(Latent Dirichlet Allocation) 알고리즘을 통한 토픽모델링 분석결과 13개의 주제 영역이 도출되었다. 셋째, 13개의 주제 영역을 네트워크로 표현한 결과 '리포지터리 구축(Repository Construction)'을 중심으로 기관간의 협력, 정보자원 보존을 위한 환경 구축, 정부차원에서의 제도와 정책 발굴, 정보자원의 생애주기, 정보자원의 전시, 정보자원의 검색 등이 서로 밀접한 관련성을 가진 것으로 나타났다. 넷째, 13개의 주제 영역의 연도별 동향을 살펴보면, 1998년 이전의 연구는 제도와 정책 발굴, 정보자원의 검색, 정보자원의 생애주기 등과 같이 특정 주제에 한정된 반면, 그 이후의 연구는 보다 다양한 주제를 다룬 것으로 분석되었다.

• 한국정보시스템학회지:정보시스템연구
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• 제18권2호
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• pp.35-59
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• 2009

The study of Information Systems(IS) is a relatively new discipline area, thus an analysis of the latest research literature could be useful to identify what the researchers are doing and what can be done to improve our discipline. With that purpose in mind, this study analyzes the total 208 articles published in "The Journal of Information Systems~ between 2001 and 2008. The classification system that comprises three key characteristics of diversity (research topic, research method, and reference discipline) was developed based on a review of prior literature. The results of this study were also compared with Kim et al.(2005)'s and Vessey et al.(2002)'s results to identify issues in current Information Systems research and 10 suggest some recommendations for future In formation Systems research. The findings identify popular research topic:s, the dominant research method, and reference discipline. The popular research topics consists of organizational concepts, problem domain-specific concepts, and systems/software management concepts. Field study was characterized as the dominant research method in the papers included in the study. Information Systems itself represents the major theoretical reference of the studies. However, many papers in this study relied on a number of reference disciplines., none of which was dominant, or they did not rely on a specific reference discipline. Finally, this study suggests more research on the disciplinary issues, more training on the research method, more accurate and specific reference discipline, and controlled diversity.

• 산업경영시스템학회지
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• 제46권3호
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• pp.170-185
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• 2023

The advent of big data has brought about the need for analytics. Natural language processing (NLP), a field of big data, has received a lot of attention. Topic modeling among NLP is widely applied to identify key topics in various academic journals. The Korean Society of Industrial and Systems Engineering (KSIE) has published academic journals since 1978. To enhance its status, it is imperative to recognize the diversity of research domains. We have already discovered eight major research topics for papers published by KSIE from 1978 to 1999. As a follow-up study, we aim to identify major topics of research papers published in KSIE from 2000 to 2022. We performed topic modeling on 1,742 research papers during this period by using LDA and BERTopic which has recently attracted attention. BERTopic outperformed LDA by providing a set of coherent topic keywords that can effectively distinguish 36 topics found out this study. In terms of visualization techniques, pyLDAvis presented better two-dimensional scatter plots for the intertopic distance map than BERTopic. However, BERTopic provided much more diverse visualization methods to explore the relevance of 36 topics. BERTopic was also able to classify hot and cold topics by presenting 'topic over time' graphs that can identify topic trends over time.

• 한국융합학회논문지
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• 제11권9호
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• pp.21-29
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• 2020

최근 디지털 사회의 도래로 다양한 데이터가 폭발적으로 증가하고, 그중 문헌 내 주제어를 도출하는 토픽 모델링에 관한 연구가 활발히 진행되고 있다. 본 논문의 연구목표는 토픽 모델링 방법 중 하나인 DTM(Dynamic Topic Model) 모델을 적용해 D.N.A.(Data, Network, A.I) 분야에 대한 연구동향을 탐색하는데 있다. 실험 데이터는 최근 6년간(2015~2020) ICT(Information and Communication Technology) 분야 중 기술대분류가 SW·AI에 해당하는 연구과제 1,519개 사업에 대해 DTM 모델을 적용하였다. 실험결과로, D.N.A. 분야의 기술 키워드 Big data, Cloud, Artificial Intelligence와 확장된 의미의 기술 키워드 Unstructured, Edge Computing, Learning, Recognition 등이 매년 연구에 표출되었으며, 해당 키워드 들이 특정 연구과제에 종속되지 않고 다른 연구과제에서도 포괄적으로 연구되고 있음을 확인하였다. 끝으로 본 논문의 연구결과는 향후 D.N.A. 분야에 대한 정책기획·과제기획 등 연구개발 기획 과정과 기업의 기술 확보전략·마케팅 전략 등 다양한 곳에 활용될 수 있을 것으로 기대한다.

• 정보관리학회지
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• 제26권2호
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• pp.105-126
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• 2009

본 연구에서는 한국과 미국의 주요 의과대학 소속 연구자들이 발표한 연구논문 주제영역을 분석함으로써, 의학 주제영역의 학제적 성격에 대한 파악과 함께 국가별 연구 주제 영역의 특성과 경향을 비교하였다. 분석 결과 저널 수로 파악된 한국 의학 연구자들의 주요 연구 영역은 CLINICAL NEUROLOGY이며 논문수로 파악된 주요 연구영역은 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING로 나타났다. 반면, 미국 의학 연구자들의 주요 연구영역은 저널 및 논문 분석 결과 모두 동일하게 BIOCHEMISTRY & MOLECULAR BIOLOGY로 나타났다. 또한 한국 연구자들은 몇몇 주제분야에서 일부 저널에 논문을 다수 게재하는 출판경향이 있는 것으로 나타났다.

• 대한예방한의학회지
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• 제15권1호
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• pp.17-27
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• 2011

Objective : The purpose of this study was to identify the trend of research in the Korean Journal of Oriental Preventive Medicine and to suggest future perspective for oriental preventive medicine research. Method : The contents of 344 articles published in this journal was reviewed from its beginning year 1997 to year 2010. Result : The number of articles was increased as times go on. An analysis of the research design showed, experimental research (in vivo or in vitro) was 36.9%, survey research was 26.5%, review was 20.1%. In the major classifications of topics published, health management 28.5%, oriental medicine effectiveness 25.3%, herbal safety and toxicity 13.1%, and environmental and occupational medicine 9.0% respectively. Conclusion : There has been a lack of health preservation(Yang-saeng) topic, epidemiology and health statistics topic. Further research need qualitative study and each subjects of oriental preventive medicine.

• 사상체질의학회지
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• 제22권3호
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• pp.67-74
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• 2010

1. Objectives: The research papers published by researchers in other fields except Oriental medicine were analyzed to study the research trends and characteristic of Sasang Constitutional medicine. 2. Methods: Systematic searches were performed on KISS, RISS, KISTI and DBPIA and finally 123 papers were selected. The publication year, research field of the first author, title's characteristic, research topic and the classification method of Sasang Constitution were investigated. 3. Results and conclusions: 1) In the analysis of publication year, the number of studies on Sasang Constitution has increased dramatically since 2000. 2) In the analysis of the first author's research field, physical training, nursing, engineering and food and nutrition were the majority. 3) In the analysis of the research topic, the classification method of Sasang Constitution was the majority. 4) In the analysis of the classification method of Sasang Constitution, QSCC II was the most popular method accounted for 68% and interview by specialist of Sasang Constitutional medicine accounted for 42%.

• 한국생활과학회지
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• 제19권5호
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• pp.817-833
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• 2010

This study was dedicated to searching better course of low birth rate study in Korea by carefully analyzing past and present low birth rate researches. For this 179 studies(101 master thesis and 78 journal articles) from 1991 to 2009 were analyzed. Next, using SPSS Win 12.0, the research type, topic, participants, data collection and method of data analysis were compared to the studies' years of publication. The most frequently applied research approach, topic, sampling method, data collection procedure and data analysis method in the research was found to be a literature study, solution and prevention of low birth rate related policy, literature study, literacy analysis. In conclusion, low birth rate studies should become more diversified in terms of types of the research, data collection method, and data analysis. Additionally, research topics should become more realistic and specified. Moreover, research results should be verified before they are applied to the policy.

• 한국IT서비스학회지
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• 제15권3호
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• pp.157-171
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• 2016

As unemployment rates and concerns about turnover keep growing, the need for information is also increasing. In these situations, the job reviews which share information about the company catch people's attention because they are usually created by people who worked at the company. The development of SNS and mobile environments has led to an increase in the web services that provide job reviews. For example, Jobplanet is a job review service in Korea, and Glassdoor.com offers a similar service in the US. Despite this attention, however, research utilizing job reviews is insufficient. This paper asks whether there are differences in ratios of job satisfaction factors by industry, using LDA topic modeling and co-occurrence analysis to explore the differences. Through the results of LDA, we find that the ratios of job satisfaction factors are similar by industry. At the same time, the results of co-occurrence analysis show that the co-occurrence frequency of some job satisfaction factors appears high: pay and welfare, balance of work and life, company culture. We expect that the result of this research will be helpful in comparative analysis of job satisfaction factors by industry. Furthermore, in this paper we suggest how to use the job review data in organizational behavior research.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제14권5호
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• pp.507-511
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• 2008

과학기술 분야는 매우 빠른 발전 속도를 보이며 세부 분야 간 융 복합 현상이 빈번하게 일어나는 특징을 가지고 있다. 과학기술정보 말뭉치로부터 상기 특성을 분석해 내는 작업은 연구 주제 추이를 분석하고 주제 간 연관 관계를 파악하기 위해 필요하다. 본 연구는 과학기술 분야 - 특히 정보기술(Information Technology) 분야 - 에서 광범위하게 활용되고 있는 Citeseer 말뭉치로부터 추출된 주제를 이용하여 다양한 주제 분석을 수행하는 방안을 보이는 것을 목표로 한다. 특히, 연구개발 전주기 지원 시스템인 OntoFrame에서 주제가 어떠한 역할을 할 수 있는지 사례를 통해 실증하고자 한다.