• Journal of the Korean Society for Library and Information Science
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• v.38 no.1
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• pp.173-197
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• 2004

It is searched that 56 out of 185 university libraries(30.2%) has adopted 'subject specialization' organization. This 'subject specialization' emerged when university libraries began to care about their users and services for them more than other factors in planning and structuring their organization. The number of university libraries which try to adopt that organization has been continuously increasing. To settle 'subject specialization' in the university libraries under Korea's proper condition and to maximize its effect, each library should consider one's own conditions and step the reasonable procedure in adopting that system. Considering the similar condition which the university libraries in Korea face such as shortage of material support, 'Mixed Model of subject specialization" is reasonable, which means in whole structure of library function-oriented organization is adopted and in Reference Service, subject specialization is adopted. However, the ideal and final destination of Korea's university libraries is the adoption of 'Full subject specialized model": it can be reached when they are supported by sufficient human resources and good conditions.

• Proceedings of the KAIS Fall Conference
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• 2012.05a
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• pp.289-292
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• 2012

본 논문에서는 1940년대 할리우드 영화 <우리 생애 최고의 해>의 '귀향 장면'의 주제를 연구하였다. 그 장면 속에 제시되는 몇 개의 주제의 음악적 성격과 그 주제가 반복되고 변형되는 스타일을 분석함으로써 작곡가가 영화의 장면에 대응하는 방법을 밝히고자 하였다. 여기서 작곡가 프리드호퍼는 주제의 반복과 변형, 특정 음정과 분산화음의 빈번한 사용, 조성구조에서의 해결 지연과 화음의 연장이라는 방법을 주인공들의 심리 묘사에 사용한다.

• Journal of Information Management
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• v.39 no.4
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• pp.121-154
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• 2008

In this paper, a ontology-based keyword structuring method is proposed to represent the knowledge structure of scholarly documents and to make inferences from the semantic relationships holding among them. The characteristics of thesaurus as a knowledge organization system(KOS) for subject heading is critically reviewed from the information retrieval point of view. The domain concepts are identified and classified by analysis of the information activities occurring in a general research process based on scholarly sensemaking model. The ontological structure of keyword set is defined in terms of the semantic relationship of the canonical concepts which constitute scholarly documents such as journal articles. As a result, each ontologically structured keyword set of a document represents the knowledge structure of the corresponding document as semantic index. By means of the axioms and inference rules defined for information needs, users can efficiently explore the scholarly communication network built on the semantic relationship among documents in an analytic way based on the scholarly sensemaking model in oder to efficiently retrieve the relevant information for problem solving.

• Journal of the Korean Society for information Management
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• v.27 no.4
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• pp.7-32
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• 2010

The aims of this study were to provide a global overview of research trends in information science and to trace its changes in the main research topics over time using trends analysis. The study examined the topics of research articles published in Journal of Korean Society for Information Management between 1984 and 2009. Rather than taking a single snapshot of a given point in time, this study attempted to present a series of such pictures in order to identify trends over time. The fairly arbitrary decision was taken to divide the period under consideration into three 'publication windows': 1984-1994, 1995-2002, 2003-2009. The study revealed that the most productive areas were 'Information Service', followed by 'Information Organization', and 'Information System'. The most productive sub-areas were 'Library Service', 'User Study', 'Automatic Document Analysis', 'ILS', 'Thesaurus/Ontology', and 'Digital Library'. From the comparisons of intellectual structures of title keywords, the key research area in the field of Information Science was 'Information Retrieval'. The studies of IT applications and service system evaluation have been expanded.

• Journal of Information Management
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• v.43 no.2
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• pp.43-66
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• 2012

The purpose of this study is to see the intellectual structure in the field of veterinary sciences in Korea, using author profiling analysis(APA), a bibliometric approach. Three journals are selected on the basis of citation data, exchanging most citations with Korean Journal of Veterinary. And then, 50 authors who published most articles at selected journals during the given period of time were chosen. The analysis of similarity and dissimilarity among authors by comparing co-word appearance patterns from article title, abstracts, and keywords was made. Authors can be grouped 11 minor clusters under 4 major clusters, depending on their interests in the area of veterinary sciences in Korea. The subjects for each cluster at the veterinary sciences are decided by the matching the keyword, representing author's research interest. As a result, it is possible to figure out the current research trends and the researcher network in the field of veterinary sciences.

• 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 Intelligence and Information Systems
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• v.13 no.4
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• pp.17-34
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• 2007

Organizations have realized the importance of CRM. To obtain the maximum possible lifetime value from a customer base, it is critical that customer data is analyzed to understand patterns of customer response. As customer databases assume gigantic proportions due to Internet and e-commerce activity, data-mining-based market segmentation becomes crucial for understanding customers. Here we raise a question and some issues of using single SOM approach for clustering while proposing multiple self-organizing maps approach. This methodology exploits additional themes on the attributes that characterize customers in a typical CRM system. Since this additional theme is usually ignored by traditional market segmentation techniques we here suggest careful application of SOM for market segmentation.

• 재활복지
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• v.21 no.1
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• pp.1-26
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• 2017

The main purpose of this paper is identifying the trends of researches in the realm of social welfare for disabled people. It tries to introduce an alternative analytic approach - key word network analysis - that might surpass the shortage of analysis methods of existing studies which have mainly relied on descriptive analysis. For this purpose the authors constructed a database composed of key words and informations about research methods of the data sources of this study. The sources are such researches as doctoral theses and the papers of Korean Journal of Social Welfare and Journal of Rehabilitation Research which were published during the 20 years from 1996 to 2015. Total numbers of the thesis or papers analysed at this study are 1,034. The results are shown in three ways as follows: First, the method trends of selected researches. Second the lists of interested types and population groups of the disabled persons and interested issues. Third, the intellectual structure of the research. Based on the findings of this study, some suggestions are given considering desirable directions of future researches in relation to perspectives, methods, targets and subjects of them.

• Journal of the Korean Society for information Management
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• v.26 no.2
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• pp.195-210
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• 2009

This study explores knowledge structures of science and technology disciplines using a cocitation analysis of journal subject categories with the publication data of a science & technology oriented university in Korea. References cited in the articles published by the faculty of the university were analyzed to produce MDS maps and network centralities. For the whole university research domain, six clusters were created including clusters of Biology related subjects, Medicine related subjects, Chemistry plus Engineering subjects, and multidisciplinary sciences plus other subjects of multidisciplinary nature. It was found that subjects of multidisciplinary nature and Biology related subjects function as central nodes in knowledge communication network in science and technology. Same analysis procedure was applied to two natural science disciplines and another two engineering disciplines to present knowledge structures of the departmental research domains.

• Journal of KIISE
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• v.44 no.2
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• pp.139-147
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• 2017

Most of the information prevailing in the Internet space consists of textual information. So one of the main topics regarding the huge document analyses that are required in the "big data" era is the development of an automated understanding system for textual data; accordingly, the automation of the keyword extraction for text summarization and abstraction is a typical research problem. But the simple listing of a few keywords is insufficient to reveal the complex semantic structures of the general texts. In this paper, a text-visualization method that constructs a graph by computing the related degrees from the selected keywords of the target text is developed; therefore, two construction models that provide the edge relation are proposed for the computing of the relation degree among keywords, as follows: influence-interval model and word- distance model. The finally visualized graph from the keyword-derived edge relation is more flexible and useful for the display of the meaning structure of the target text; furthermore, this abstract graph enables a fast and easy understanding of the target text. The authors' experiment showed that the proposed abstract-graph model is superior to the keyword list for the attainment of a semantic and comparitive understanding of text.