• Journal of the Korean Society for Library and Information Science
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• v.44 no.2
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• pp.285-308
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• 2010

This study analyzes the intellectual structure in domestic research of the Housing field, by utilizing text mining technique. Unlike the existing research that mainly uses text clustering in statistical analyses to identify subject specialties, core authors, and relationships between research areas, this study applied author profiling and factor analysis. To supplement the analysis of intellectual structure generated by text mining, and to perform evaluation on intellectual structure itself, two professionals in the housing field were interviewed. The intellectual structure, generated through text mining, was evaluated and showed its division of valid research areas that is slightly different from the traditional intellectual structure in the housing field.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.115-140
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• 2021

This study divided the keyword sets searched from LISTA database focusing on the overseas open access fields into two types (controlled keywords and uncontrolled keywords), and examined the results of performing an intellectual structure analysis based on profiling for the each keyword type. In addition, these results were compared with those of an intellectual structural analysis based on co-word analysis. Through this, I tried to investigate whether similar results were derived from profiling, another method of intellectual structure analysis, and to examine the differences between co-word analysis and profiling results. As a result, there was a similar difference to the co-word analysis in the results of intellectual structure analysis based on profiling for each of the two keyword types. Also, there were also noticeable differences between the results of intellectual structural analysis based on profiling and co-word analysis. Therefore, intellectual structure analysis using keywords should consider the characteristics of each keyword type according to the research purpose, and better results can be expected to be used based on profiling than co-word analysis to more clearly understand research trends in a specific field.

• Journal of the Korean Society for information Management
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• v.30 no.4
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• pp.31-59
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• 2013

The purpose of this study was to examine the intellectual structure of domestic LIS in the 1990s and 2000s using author bibliographic coupling analysis (ABCA). First, cluster analysis and multi-dimensional scaling analysis were performed to examine core subject areas and to map authors in two-dimensional space. Second, network analysis was used to visualize intellectual relationships among subject areas and to reveal the top subject areas for global centrality. Third, the 1990s and 2000s intellectual structures was compared to identify the changes of the intellectual structure over the course of time.

• Journal of the Korean Society for information Management
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• v.27 no.3
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• pp.283-306
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• 2010

This study intended to make new suggestions by clarifying usefulness of analysis methodology for the intellectual structure of disciplines, which combines author co-citation analysis and author bibliographic coupling analysis. It also aimed to identify the recent research trend and key researchers recently doing research activities actively as well as the intellectual structure in the field of social welfare. It was found to be more efficient to conduct both author co-citation analysis and author bibliographic coupling analysis in order to identify traditional sub-areas of disciplinary subject or the research trend of actual researchers in examining the intellectual structure of a specific discipline.

• Journal of the Korean Society for information Management
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• v.28 no.1
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• pp.123-144
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• 2011

This study compared Author Profiling Analysis(APA) to Author Co-Citation Analysis (ACA). The former is a new analytic technique on the intellectual structure of a science whereas the latter is a traditional analytic technique. The purpose of this study was to propose appropriate methods to analyze intellectual structure of a science in the Korean research environment. In order to achieve the goal, this study adopted APA using Text Mining for analysis on the intellectual structure of a science rather than relying on citation index in order to determine a potential utility of the new analytic technique that can identify the intellectual structure.

• Journal of Korean Academy of Nursing Administration
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• v.18 no.4
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• pp.452-459
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• 2012

Purpose: This study was a descriptive study conducted to investigate the effects of intellectual capital on organizational performance of nurses in medium and small hospitals. Methods: Data were collected from 241 nurses working in medium and/or small hospitals located in G City from August 10 to September 17, 2011. The measurement tools were the Intellectual Capital scale and Organizational Performance scale. Data were analyzed using frequency, percentage, mean, standard deviation, t-test, one way ANOVA, Pearson correlation, and hierarchical regression with SPSS WIN 18.0 PC. Results: Intellectual capital composed of human, customer, and structure capital had significant effects on organizational performance of nurses working in medium and small hospitals and explained 50.4% of the variance. Conclusion: In order to promote organizational performance of nurses, nursing managers and administrators need to invest more resources into the intellectual capital of the system including human, customer, and structure capital.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.2
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• pp.333-355
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• 2006

Network generation methods to visualize bibliometric data for examining the intellectual structure of knowledge domains are investigated in some detail. Among the four methods investigated in this study, pathfinder network algorithm is the most effective method in representing local details as well as global intellectual structure. The nearest neighbor graph, although never used in bibliometic analysis, also has some advantages such as its simplicity and clustering ability. The effect of input data preparation process on resulting intellectual structures are examined, and concluded that unlike MDS map with clusters, the network structure could be changed significantly by the differences in data matrix preparation process. The network generation methods investigated in this paper could be alternatives to conventional multivariate analysis methods and could facilitate our research on examining intellectual structure of knowledge domains.

• Journal of the Korean Society for information Management
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• v.20 no.3
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• pp.277-297
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• 2003

This study was conducted upon the premise that index terms display the intellectual structure of a specific subject field. In this study, and attempt was made to grasp the intellectual structure of Library and Information. Science by clustering the index terms of the journals of the related academic societies at the Library of National Assembly - such as the Journal of the Korean Society for Information Management, the Journal of the Korean Library and Information Science Society, and the Journal of the Korean Society for Library and Information Science. Through the course of the study, index term clusters were generated based on the linkage of the index terms and the frequency of co-occurrence, and moreover, time periods analysis was conducted along with studies on first-appearing terms, in order to clarify the trend and development process of the Library and Information Science. This study also analysed the difference between two intellectual structure by comparing the structure generated by index term clusters with the existing structure of traditional classification systems.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.309-330
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• 2022

Intellectual structure analysis, which quantitatively identifies the structure, characteristics, and sub-domains of fields, has rapidly increased in recent years. Analysis techniques traditionally used to conduct intellectual structure analysis research include bibliographic coupling analysis, co-citation analysis, co-occurrence analysis, and author bibliographic coupling analysis. This study proposes a novel intellectual structure analysis method, Keyword Bibliographic Coupling Analysis (KBCA). The Keyword Bibliographic Coupling Analysis (KBCA) is a variation of the author bibliographic coupling analysis, which targets keywords instead of authors. It calculates the number of references shared by two keywords to the degree of coupling between the two keywords. A set of 1,366 articles in the field of 'Open Data' searched in the Web of Science were collected using the proposed KBCA technique. A total of 63 keywords that appeared more than 7 times, extracted from 1,366 article sets, were selected as core keywords in the open data field. The intellectual structure presented by the KBCA technique with 63 key keywords identified the main areas of open government and open science and 10 sub-areas. On the other hand, the intellectual structure network of co-occurrence word analysis was found to be insufficient in the overall structure and detailed domain structure. This result can be considered because the KBCA sufficiently measures the relationship between keywords using the degree of bibliographic coupling.

• Journal of Korea Technology Innovation Society
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• v.2 no.1
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• pp.90-103
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• 1999

This article is dedicated to present a cornerstone for a desirable legal structure in the area of the administration and utilization of the intellectual property rights of the university research results sponsored by the government, and, in the long run, contribute to the industrial development of our country. In order to achieve that purpose, this article reviews basic theories and current status of the intellectual property regime for the research results sponsored by the government, and presents some suggestions for a desirable legal institution, in particular, including that 'Intellectual Property Rights Administration Center', should be established, an exclusive institution for the systematic administration of the follow-ups of the research results with speciality.