• Proceedings of the Korean Society for Information Management Conference
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• 2006.08a
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• pp.145-152
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• 2006

저자동시인용분석 기법은 인용을 통해서 특정 주제분야의 지적 구조를 파악하는 수단으로 널리 사용되고 있다. 그러나 저명한 연구자 위주의 분석이 되기 쉬우므로 은퇴자나 고인을 비롯한 비현역 연구자가 포함되는 경우도 흔하다. 또한 비영어권 국가의 국내 연구동향을 분석할 경우에는 분석결과에 국내 연구자가 상당수 배제되는 상황도 발생한다. 이 연구에서는 국내 현역 연구자 위주로 최근 동향을 분석할 수 있는 새로운 지적 구조 분석법인 서지적 저자결합분석을 제안하고 실제 자료를 대상으로 분석하여 효용성을 검증하였다

• Journal of the Korean Society for Library and Information Science
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• v.41 no.2
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• pp.335-357
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• 2007

There has been many studies representing intellectual structures with multidimensional scaling(MDS) However MDS configuration is limited in representing local details and explicit structures. In this paper, we identified two components of MDS mapping approach; one is MDS algorithm and the other is preparation of data matrix. Various combinations of the two components of MDS mapping are compared through some measures of fit. It is revealed that the conventional approach composed of ALSCAL algorithm and Euclidean distance matrix calculated from Pearson's correlation matrix is the worst of the compared MDS mapping approaches. Otherwise the best approach to make MDS map is composed of PROXSCAL algorithm and z-scored Euclidean distance matrix calculated from Pearson's correlation matrix. These results suggest that we could obtain more detailed and explicit map of a knowledge domain through careful considerations on the process of MDS mapping.

• Proceedings of the Korean Society for Information Management Conference
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• 2005.08a
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• pp.349-356
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• 2005

지적 구조 분석을 위해서 계량서지적 자료를 시각적으로 표현하는 다양한 네트워크 형성 방식에 대해서 사례와 함께 각각의 특성을 살펴보았다. 동시인용을 비롯한 계량서지적 자료의 시각적인 표현은 지적구조의 분석에 있어서 매우 효과적인 방법으로 인식되어왔다. 시각화를 위해서는 전통적으로 다차원척도법이나 군집분석, 대응일치분석 등의 다변량통계 분석 기법이 사용되어왔다. 최근 들어 패스파인더 네트워크를 비롯한 새로운 네트워크 형성 기법이 전통적인 기법의 대체 도구로 제시되고 있으나, 사실상 네트워크의 형태로 지적 구조를 분석하는 것은 인용분석 연구의 초기부터라고 할 수 있다. 다양한 네트워크 형성 방식의 특성에 대해서 살펴봄으로써 계량서지적 분석을 활성화하는데 도움이 되리라고 기대한다.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.147-178
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• 2021

In this study, co-word analysis was conducted to investigate the intellectual structure of the domestic open access area. Through KCI and RISS, 124 research articles related to open access in Korea were selected for analysis, and a total of 1,157 keywords were extracted from the title and abstract. Network analysis was performed on the selected keywords. As a result, 3 domains and 20 clusters were extracted, and intellectual relations among keywords from open access area were visualized through PFnet. The centrality analysis of weighted networks was used to identify the core keywords in this area. Finally, 5 clusters from cluster analysis were displayed on a multidimensional scaling map, and the intellectual structure was proposed based on the correlation between keywords. The results of this study can visually identify and can be used as basic data for predicting the future direction of open access research in Korea.

• Spatial Information Research
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• v.17 no.4
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• pp.469-481
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• 2009

Due to the increasing demands on the efficient use of land and the fast growth of construction technologies, human living space is expanded from on the surface to above and under the surface. By recognizing that the current cadastre system based on 2D was not appropriate to reflect the trend, the researchers are interested in a 3D cadastre. This paper proposed the 3D cadastre data model that is appropriate to protect ownership effectively in Korea. The 3D cadastre data model consists of a 3D cadastre feature model and a 3D cadastre geometry model, and the data are produced by a 3D cadastre data structure. A 3D cadastre feature model is based on 3D rights and features derived from case studies. A 3D cadastre geometry model based on ISO19107 Spatial Schema is modified to be good for 3D cadastre in Korea. A 3D cadastre data structure consists of point, line, polygon and solid primitives. This study finally purposes 1) serving and managing land information effectively, 2) creating rights and displaying ranges about infrastructures above and under surface, 3) serving ubiquitous-based geoinformation, 4) adapting ubiquitous-based GIS to urban development, and 5) regulating relationships between rights of land and registration and management 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 rehabilitation welfare engineering & assistive technology
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• v.11 no.1
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• pp.15-20
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• 2017

The purpose of this study is to present the intellectual structure of Assistive Technology Journal using co-word analysis of keywords. The articles of Assistive Technology Journal were collected from Web of Science citation database. 255 articles during the period from 2003 to 2015 were selected for the analysis. And 1,359 author keywords were extracted from the articles. In order to analyze the intellectual structure of Assistive Technology Journal, clustering analysis was conducted and 5 clusters were determined. Next, 5 clusters are presented in the map of multidimensional scaling. The results of this study are expected to assist in exploring the future directions of the researches on assistive technology.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.99-113
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• 2013

The study investigated the intellectual structure of the library and information science field by journal co-citation analysis on thirty LIS journals with high journal impact factors. Patterns of journal-to-journal citation show the structure of journals in the field, visualized by a networked map of the journals. The result shows journals that can be considered as the core group and as the peripheral group, which corresponds to other studies for investigating the field's intellectual structure using other techniques, such as cluster analysis and multidimensional scaling.

• 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.23 no.4 s.62
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• pp.215-231
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• 2006

Recently there are many bibliometric studies attempting to utilize Pathfinder networks(PFNets) for examining and analyzing the intellectual structure of a scholarly field. Pathfinder network scaling has many advantages over traditional multidimensional scaling, including its ability to represent local details as well as global intellectual structure. However there are some limitations in PFNets including very high time complexity. And Pathfinder network scaling cannot be combined with cluster analysis, which has been combined well with traditional multidimensional scaling method. In this paper, a new method named as Parallel Nearest Neighbor Clustering (PNNC) are proposed for complementing those weak points of PFNets. Comparing the clustering performance with traditional hierarchical agglomerative clustering methods shows that PNNC is not only a complement to PFNets but also a fast and powerful clustering method for organizing informations.