• Journal of the Korean Society for information Management
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• v.22 no.1 s.55
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• pp.191-208
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• 2005

This study utilizes various approaches for new topic detection in the process of assigning and updating descriptors, which is a representation method of the knowledge structure. Particularly in the case of occurring changes on the knowledge structure due to the appearance and development of new topics in specific study areas, new topic detection can be applied to solving the impossibility or limitation of the existing index terms in representing subject concepts. This study confirms that the majority of newly developing topics in information science are closely associated with each other and are simultaneously in the phase of growth and development. Also, this study shows the possibility that the use of candidate descriptor lists generated by new topic detection methods can be an effective tool in assisting indexers. In particular. the provision of candidate descriptor lists to help assignment of appropriate descriptors will contribute to the improvement of the effectiveness and accuracy of indexing.

• Journal of the Korean Society for Library and Information Science
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• v.36 no.3
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• pp.5-23
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• 2002

With the rapid change of information environment, this study suggests role models and strategies for the university library in Korea based on the subject specialization. By analyzing the current situation and problems of university library, this research presents various directions for the subject specialization. Major research issues are (1) university library's subject specialization directions, models, and factors, (2) subject specialized librarian' s role and education system, (3) basic framework for customized information service and user education, (4) enhancement of subject specialization through subject gateway, (5) academic information sharing system.

• 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.38 no.3
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• pp.1-22
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• 2021

An online experiment was conducted to test the subject-knowledge view of relevance theory in order to find evidence of a conceptual basis for relevance. Six experts in Library and Information Science (LIS), nine Master's students of LIS, and twelve non-experts judged the relevance of 14 abstracts within and outside of the LIS domain. Consistency among the judges was calculated by joint-probability agreement (PA) and interclass correlation coefficients (ICC). When using PA to analyze the judgements, non-experts had a higher consensus regardless of the task or division of groups. However, ICC calculations found Master's candidates had a higher level of consensus than non-experts within LIS, although the experts did not; and the agreement rates on the non-LIS task for all groups were only poor to moderate. It was only when the groups were analyzed as two groups (experts including Master's candidates and non-experts) that the expected trend of higher consistency among experts in the LIS task was seen.

• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.123-142
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• 2012

To develop an intelligent search engine to help users retrieve information effectively, various methods, such as Semantic Web, have been used, An effective retrieval method of such methods uses ontology technology. In this paper, we built National R&D ontology after analyzing National R&D Information in NTIS and then implemented National R&D Knowledge Map to represent and retrieve information of the relationship between object and subject (project, human information, organization, research result) in R&D Ontology. In the National R&D Knowledge Map, center-node is the object selected by users, node is subject, subject's sub-node is user's favorite query in National R&D ontology after analyzing the relationship between object and subject. When a user selects sub-node, the system displays the results from inference engine after making query by SPARQL in National R&D ontology.

• KOREAN POULTRY JOURNAL
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• v.20 no.6 s.224
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• pp.99-101
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• 1988

미국달걀위원회에서 편찬한 책으로 '달걀교육의 백과사전과정'이라고도 불린다. 이 책을 다시 설명하면 달걀지식을 폭넓게 다루었고 이와 관련된 모든 분야의 정보를 수록하였으며 각 주제별 알파벳순으로 정리 되었다. 또한 달걀에 관련된 주제에 대해 정의와 설명을 붙였으며 이의 이해를 돕기위해 도해, 도표, 그래프 등을 적절히 사용한 소책자라고 할 수 있다. 본지는 독자들의 계란에 대한 올바르고 폭넓은 지식을 얻을 수 있도록 연재로 소개한다.

• KOREAN POULTRY JOURNAL
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• v.20 no.5 s.223
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• pp.100-104
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• 1988

미국달걀위원회에서 편찬한 책으로 '달걀교육의 백과사전과정'이라고도 불린다. 이 책을 다시 설명하면 달걀지식을 폭넓게 다루었고 이와 관련된 모든 분야의 정보를 수록하였으며 각 주제별 알파벳순으로 정리 되었다. 또한 달걀에 관련된 주제에 대해 정의와 설명을 붙였으며 이의 이해를 돕기위해 도해, 도표, 그래프 등을 적절히 사용한 소책자라고 할 수 있다. 본지는 독자들의 계란에 대한 올바르고 폭넓은 지식을 얻을 수 있도록 연재로 소개한다.

• KOREAN POULTRY JOURNAL
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• v.20 no.1 s.219
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• pp.99-102
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• 1988

미국달걀위원회에서 편찬한 책으로 '달걀교육의 백과사전과정'이라고도 불린다. 이 책을 다시 설명하면 달걀지식을 폭넓게 다루었고 이와 관련된 모든 분야의 정보를 수록하였으며 각 주제별 알파벳순으로 정리되었다. 또한 달걀에 관련된 주제에 대해 정의와 설명을 붙였으며 이의 이해를 돕기위해 도해, 도표, 그래프 등을 적절히 사용한 소책자라고 할 수 있다. 본지는 독자들의 계란에 대한 올바르고 폭넓은 지식을 얻을 수 있도록 연재로 소개한다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.151-153
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• 2000

현재의 자동 문서 분류 시스템에서는 문서분류는 지식베이스를 구축하고 전문가가 클레스의 분류 주제어를 수동 입력함으로써 이루어진다. 이것은 대단히 어렵고 번거로운 일이며 많은 시간과 노력이 소요되고 지속적으로 이루어지기 힘들다. 본 논문에서는 지식베이스와 문서의 구조적 정보, 통계적 정보, 키워드 간의 응집도를 이용하여 자동 문서 분류를 위한 분류 주제어의 자동 증식 방법을 제안한다.

• 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.