• Proceedings of the Korean Society for Information Management Conference
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• 2017.08a
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• pp.11-14
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• 2017

딥러닝 연구동향에 대한 계량서지적 분석을 자아 중심 주제 인용분석 기법을 활용하여 시도하였다. 이를 위해서 Web of Science에서 'deep learning'으로 검색된 인용빈도 상위 15건의 논문을 핵심 논문으로 삼고, 이들 핵심 논문 15편을 인용한 논문 집합을 자아 문헌집합으로 삼았으며, 자아 문헌집합들이 인용한 주요 문헌들을 인용 정체성 문헌집합으로 설정하였다. 인용 정체성 문헌집합에 대해 동시인용분석을 실시하여 주요 문헌, 주요 연구 주제를 파악하고, 영향을 끼친 주요 선행 연구를 파악해보았다.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.119-143
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• 2011

This study identifies the characteristics of recent citation-based indicators for assessing a single paper in the context of their co-relationships. Five predefined indicators were examined with three variants of h-index which are convened in this study; the formers are PageRank, SCEAS Rank, CCI, f-value, and single paper h-index and the latters are $h_S$-index, h1-index, and $h_S$1-index. The correlation analysis and cluster analysis were performed to group the indicators by common characteristics, after which the indicators were calculated with the dataset from KSCI DB. The results show statistical evidence that distinguishes h-index type indicators from others. The characteristics of the indicators were verified with citation frequency factors using correlation analysis. Finally, the implications for applications and further studies are discussed.

• Proceedings of the Korean Society for Information Management Conference
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• 2005.08a
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• pp.205-212
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• 2005

본 연구의 목적은 전문도서관인 공무원교육원 도서관의 공동수서정책을 위해 이용자의 요구를 인용문헌분석을 통해 파악하고자 하였다. 이을 위해 3개 공무원교육원의 주이용자인 장기교육생의 인용문헌을 자료의 유형분석, 자료의 최신성 분석, 인용문헌수 분석, 외국문헌 이용현황과 핵심자료를 파악하고자 하여 공무원교육원 도서관의 공동수서정책에 반영하고자 하였다. 그 결과 형태별로는 연구보고서의 인용율이 가장 높았으며, 평균인용건수를 분석한 결과, 교육수료보고서의 1인당 평균인용건수는 29.42권으로 조사되었다. 발행시기별로 분석한 결과, 출판 후2${\sim}$5년 내의 자료를 40.6%로 가장 많이 인용하는 것으로 조사되었으며, 언어별 분석 결과, 국내서로 기술된 문헌의 인용율은 90.1%로 조사되었다. 핵심자료를 파악한 결과 단행본의 최대 피인용문헌빈도(3회 이상)는 155권 이었으며, 학술지는 112종, 통계자료는 34권이었다.

• Journal of the Korean Society for information Management
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• v.41 no.2
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• pp.1-18
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• 2024

This study aims to compare ego-centered journal citation identities among four domestic journals in library and information science. Ego-centered citation identity refers to the set of authors that an author frequently cites. The target journals for this study are Journal of the Korean Society for Library and Information Science (KSLIS), Journal of the Korean Biblia Society for Library and Information Science (KBIBLIA), Journal of Korean Library and Information Science Society (KLISS), and Journal of the Korean Society for Information Management (KOSIM). As a result of citation/citee ratio (CCR), self-citing rates (SCR), and journal co-cited analysis, the journal citation identities of four journals contained the other three journals besides the ego journal and JASIST. Furthermore, KOSIM had the most diverse range of journal citation identity and the four journals mattered the intra-journal information. KLISS showed the most unique cited journal network structure among the four journals.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.4
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• pp.221-238
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• 2020

This study aims to investigate the scholarly communications and citation influences in library and information science field by conducting journal citation network analysis. For data collection, four major journals in library and information science field were chosen and 4,471 of research papers and 18,424 of citation records were collected from Korean Citation Index. The results show that Journal of the Korean Society for Library and Information Science was the most influential journal with highest citation in LIS fields, while Journal of the Korean Society for Library and Information Science Management influenced other research fields.

• Proceedings of the Korean Society for Information Management Conference
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• 2011.08a
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• pp.29-34
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• 2011

최근 인용 네트워크 분석을 통해서 단일 문헌의 인용 영향력을 측정하려는 시도가 다양하게 전개되고 있다. 널리 알려진 PageRank를 보완하려는 일부 시도와 함께 h-index를 단일 문헌의 인용 영향력 측정에 적용한 단일문헌 h-index도 제안되었다. 이 연구에서는 Web of Science에서 검색한 계량정보학 분야 문헌집합을 대상으로 여러 측정 방식의 특징을 비교해본 후, 새로운 인용지수 2종을 제안하였다. 제안한 인용지수는 PageRank처럼 전역 네트워크 분석 방식인 지수 1종과 h-index처럼 지역 네트워크 분석 방식인 지수 1종으로서 상황에 따라 선택하여 사용할 수 있다.

• Journal of the Korean Society for information Management
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• v.5 no.1
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• pp.104-130
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• 1988

The purpose of this study is to grasp the research activities of Korean statisticians and scientific properties of statistics field guantitatively by analyzing its literature with various bibliometric research methods. In this study the productivity of authors arid cited literatures were analyzed.

• Proceedings of the Korean Society for Information Management Conference
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• 2012.08a
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• pp.153-156
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• 2012

White가 제안한 자아 중심 인용 분석은 연구자를 대상으로 다면적인 분석을 가능하게 하는 방법이다. 이 연구에서는 자아 중심 인용 분석을 연구자 단위가 아닌 연구 주제에 대한 분석으로 응용하는 자아 중심 주제 인용 분석 기법을 제안하고, 시험적으로 폭소노미 주제의 연구문헌 집단에 응용하여 관련 연구의 핵심 문헌들과 주요 적용 이론을 반영하는 인용 정체성과 인용 이미지를 파악해보았다.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.4
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• pp.311-331
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• 2023

This study attempted to explore the characteristics of knowledge communication and investigate important research topics and key authors by analyzing major academic papers in the field of LIS in Korea for five years from 2018 to 2022. The research method collected and analyzed papers published for five years in four key journals in the field of domestic Library and Information Science from the Korean Citation Index (KCI) database. The paper was selected to extract the author data of the paper and the data of the reference, and network visualization was performed by conducting literature co-citation analysis and author co-citation analysis using Netminer. As a result of the analysis, it was possible to derive a pair of co-citations between authors, and it was confirmed that it is important to include multiple authors in the intellectual structure analysis in the academic field through co-citation frequency analysis among researchers. The literature confirmed the correlation between the topics of the paper, and it was found that research related to Library and Information Science was centered on the topics of library, digital, user, service, and data.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.7-32
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• 2017

Recently, deep learning has been rapidly spreading as an innovative machine learning technique in various domains. This study explored the research trends of deep learning via modified ego centered topic citation analysis. To do that, a few seed documents were selected from among the retrieved documents with the keyword 'deep learning' from Web of Science, and the related documents were obtained through citation relations. Those papers citing seed documents were set as ego documents reflecting current research in the field of deep learning. Preliminary studies cited frequently in the ego documents were set as the citation identity documents that represents the specific themes in the field of deep learning. For ego documents which are the result of current research activities, some quantitative analysis methods including co-authorship network analysis were performed to identify major countries and research institutes. For the citation identity documents, co-citation analysis was conducted, and key literatures and key research themes were identified by investigating the citation image keywords, which are major keywords those citing the citation identity document clusters. Finally, we proposed and measured the citation growth index which reflects the growth trend of the citation influence on a specific topic, and showed the changes in the leading research themes in the field of deep learning.