• Title/Summary/Keyword: 문헌동시인용

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Intellectual Structure of Korean Library and Information Science in 1990s Using Author Co-citation Analysis (저자동시 인용분석에 의한 1990년대 한국문헌정보학의 지적구조에 관한 연구)

  • 윤구호;서말숙
    • Journal of Korean Library and Information Science Society
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    • v.32 no.3
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    • pp.169-197
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    • 2001
  • This study investigated the intellectual structure of Korean library and information science and its change in the 1990s using author co-citation analysis. The citation data came from in 3 journals in the field of library and information science from 1990 through 1999, and 50 authors were selected and analyzed in detail by means of multi-variate statistical techniques such as multidimensional scaling, cluster analysis, factor analysis and crosstab analysis in order to excess the intellectual structure of discipline and its changing research patterns.

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Exploring a Researcher's Personal Research History through Self-Citation Network and Citation Identity (자기 인용 네트워크와 인용 정체성을 이용한 연구자의 연구 이력 분석에 관한 연구)

  • Lee, Jae-Yun
    • Journal of the Korean Society for information Management
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    • v.29 no.1
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    • pp.157-174
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    • 2012
  • This paper compares two recent methods for exploring a scientist's research history: citation identity and self-citation network. The former is proposed by White(2000), while the latter is suggested by Hellsten et al.(2007). An experimental citation analysis was carried out on the research output of Young Mee Chung, a renouned Korean information scientist. The result shows that the two methods divided the research period into two sub-periods in the same way. They also identified the major research themes very similarly. In the analysis of each method's performance in depth, the two methods revealed different functions to understand a researcher's history. Citation identity was useful to identify authors who have affected Chung's research in terms of research topics. whereas, self-citation network was successful to identify the core papers and leading papers of the research sub-periods. This study indicates the combination of two methods can provide rich information on a scientist's research history.

Analysis of Factors Influencing Patent Citations (특허 인용에 영향을 미치는 요인 분석)

  • Yoo, Jae-Bok;Chung, Young-Mee
    • Journal of the Korean Society for information Management
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    • v.27 no.1
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    • pp.103-118
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    • 2010
  • Recently, the valuation of patented technology has been greatly emphasized, and patent citation has been accepted as a very useful index of this technology. In this study, we performed correlation analyses between the patent citation counts and 17 explanatory variables of morphological, technological, and conceptual factors with a test dataset of U.S. patents in five subject fields. Seven variables having 5% or more standardized variances($r^2$) with patent citation counts were identified; number of pages, number of claims, reference-average-citation rate, patent increase/decrease rate, strength of bibliographic coupling, co-citation counts and document similarity. The result of the ANOVA test shows that the mean values of these variables vary among most subject fields.

Analyzing and Visualizing the Intellectual Structure of Data Science (데이터사이언스 연구의 지적 구조 분석 및 시각화)

  • Park, Hyoungjoo
    • The Journal of the Korea Contents Association
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    • v.22 no.7
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    • pp.18-29
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    • 2022
  • The purpose of this exploratory study is to examine the intellectual structure of data science. For this purpose, this research examined a total of 17,997 bibliographies on data science indexed in Web of Science(WoS) of Clarivate Analytics from 2012 to 2021. This research applied methods such as descriptive analysis, citation analysis, co-author network analysis, co-occurrence network analysis, bibliographic coupling analysis, and co-citation analysis. This research contributes to finding the research directions of future data science topics.

Detection of Knowledge Structure of Korean Studies Using Document Co-citation Analysis: the Difference between Self-perception and Others' Perception (문헌동시인용 분석을 통한 한국학 지식구조 파악: 주체 인식과 타자 인식의 차이)

  • Kim, Hea-JIn
    • Journal of Korean Library and Information Science Society
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    • v.51 no.1
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    • pp.179-200
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    • 2020
  • This study aims to detect the knowledge structure of Korean studies using document co-citation analysis and text mining techniques. This study divided Korean corpus into two perspectives: Self-perceived and others' perceived Korean studies. To this end, we collected 10,929 humanities and social literature containing the word Korea or Korean as a keyword in the SCOPUS database. As a result of analysis, a total of 20 subdomains were found in the knowledge structure of self-perception, and a total of 14 subdomains were found in the knowledge structure of otherts' perception. Differences in Korean Studies between two are: First, the sub-area of self-perceived Korean studies is subdivided into more diverse areas than the sub-area of other-perceived Korean studies. Second the major areas in self-perceived Korean studies are customers and services, industrialization, multiculturalism, mental health, tourism, Korean language, environment, and cities. Others' perceptions of Korean Studies are grouped into domestic and foreign situations of Korea, Korean pop culture, Koreans as US immigrants, and Korean language. Finally, the common areas of self-perception and others' perception were mental health, tourism, Korean language, North-Korean defectors, and juvenile delinquency.

PIV에 의한 유동장 계측

  • 이영호
    • Bulletin of the Society of Naval Architects of Korea
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    • v.31 no.2
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    • pp.43-46
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    • 1994
  • VIP는 유동장을 영상기록매체에 기록하여 보존 및 재생이 가능함으로서 유동장의 재현성문제를 쉽게 해결할 수 있는 장점을 아울러 가지고 있다. 따라서, VIP는 비정상, 동시다점 계측 및 유 동장의 재현성확보가 원리적으로 가능함으로서 CFD에 필적할 수 있는 유일한 실험기법으로 평 가되고 있다. 본 해설에서는 이에 관한 내용을 개설적으로 정리하고자 하며, 상세한 것은 참고 문헌을 인용하기로 한다.

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Subject Association Analysis of Big Data Studies: Using Co-citation Networks (빅데이터 연구 논문의 주제 분야 연관관계 분석: 동시 인용 관계를 적용하여)

  • Kwak, Chul-Wan
    • Journal of the Korean Society for information Management
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    • v.35 no.1
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    • pp.13-32
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    • 2018
  • The purpose of this study is to analyze the association among the subject areas of big data research papers. The subject group of the units of analysis was extracted by applying co-citation networks, and the rules of association were analyzed using Apriori algorithm of R program, and visualized using the arulesViz package of R program. As a result of the study, 22 subject areas were extracted and these subjects were divided into three clusters. As a result of analyzing the association type of the subject, it was classified into 'professional type', 'general type', 'expanded type' depending on the complexity of association. The professional type included library and information science and journalism. The general type included politics & diplomacy, trade, and tourism. The expanded types included other humanities, general social sciences, and general tourism. This association networks show a tendency to cite other subject areas that are relevant when citing a subject field, and the library should consider services that use the association for academic information services.

A Study on Kim Inhue's View of Reading: Through the Analysis of Reference Books in Haseo-Chunjib (하서(河西) 김인후(金麟厚)의 독서관에 관한 연구 - "하서전집"의 인용문헌 분석을 중심으로 -)

  • Ahn, Hyeon-Ju
    • Journal of Korean Library and Information Science Society
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    • v.39 no.3
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    • pp.479-500
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    • 2008
  • This study investigates Kim Inhue's view of reading through the analysis of reference books in Haseo-Chunjib(하서전집). As the result, he had read 123 different books ar least. He had quoted frequently $Sish{\bar{u}}$ $S{\bar{a}}nj{\bar{i}}ng$(사서삼경), $Sh{\check{i}}ji$(사기), $H{\grave{a}}nsh{\bar{u}}$(한서), $Zhu{\bar{a}}ngz{\check{i}}$(장자), $G{\check{u}}wenzh{\bar{e}}nb{\check{a}}o$(고문진보), $Ch{\check{u}}c{\acute{i}}$(초사), $W{\acute{e}}nxu{\check{a}}n$(문선). He had read books beyond the contemporary(sixteen centurtry) scholar's common list, and had enjoyed reading over the boundaries of stereotyped idea. While he had emphasized on the scripture of Confucian, had earned more knowledges for usefulness and the bases of scholarly writings by reading a wide spectrum of books.

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Analysis of SCI Journals Cited by Korean Journals in the Computer field

  • Kim, Byungkyu;You, Beom-Jong;Kang, Ji-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.11
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    • pp.79-86
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    • 2019
  • It is very important to analyze and provide information resources for research output produced in the computer field, the core science of the 4th Industrial Revolution. In this paper, SCI journals cited from domestic journals in the computer field were identified and the citation rankings and their co-citation networks were generated, analyzed, mapped and visualized. For this, the bibliographic and citation index information from 2015 to 2017 in the KSCD were used as the basis data, and the co-citation method and network centrality analysis were used. As a result of this study, the number of citations and the citation ranks of SCI journals and papers cited by korean journals in the computer field were analyzed, and peak time(2 years), half-life(6.6 years), and immediacy citation rate(2.4%) were measured by citation age analysis. As a result of network centrality analysis, Three network centralities(degree, betweenness, closeness) of the cited SCI journals were calculated, and the ranking of journals by each network centrality was measured, and the relationship between the subject classifications of the cited SCI journals was visualized through the mapping of the network.

An Investigation of Intellectual Structure on Data Papers Published in Data Journals in Web of Science (Web of Science 데이터학술지 게재 데이터논문의 지적구조 규명)

  • Chung, EunKyung
    • Journal of the Korean Society for information Management
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    • v.37 no.1
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    • pp.153-177
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    • 2020
  • In the context of open science, data sharing and reuse are becoming important researchers' activities. Among the discussions about data sharing and reuse, data journals and data papers shows visible results. Data journals are published in many academic fields, and the number of papers is increasing. Unlike the data itself, data papers contain activities that cite and receive citations, thus creating their own intellectual structures. This study analyzed 14 data journals indexed by Web of Science, 6,086 data papers and 84,908 cited references to examine the intellectual structure of data journals and data papers in academic community. Along with the author's details, the co-citation analysis and bibliographic coupling analysis were visualized in network to identify the detailed subject areas. The results of the analysis show that the frequent authors, affiliated institutions, and countries are different from that of traditional journal papers. These results can be interpreted as mainly because the authors who can easily produce data publish data papers. In both co-citation and bibliographic analysis, analytical tools, databases, and genome composition were the main subtopic areas. The co-citation analysis resulted in nine clusters, with specific subject areas being water quality and climate. The bibliographic analysis consisted of a total of 27 components, and detailed subject areas such as ocean and atmosphere were identified in addition to water quality and climate. Notably, the subject areas of the social sciences have also emerged.