• Proceedings of the Korean Society for Information Management Conference
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• 2017.08a
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• pp.15-18
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• 2017

학술 데이터베이스를 통해 방대한 양의 텍스트 데이터에 대한 접근이 가능해지면서, 많은 데이터로부터 중요한 정보를 자동으로 추출하는 것에 대한 필요성 또한 증가하였다. 특히, 텍스트 데이터로부터 중요한 단어나 단어구를 선별하여 자동으로 추출하는 기법은 자료의 효과적인 관리와 정보검색 등 다양한 응용분야에 적용될 수 있는 핵심적인 기술임에도, 한글 텍스트를 대상으로 한 연구는 많이 이루어지지 않고 있다. 기존의 한글 텍스트를 대상으로 한 핵심어 또는 핵심어구 추출 연구들은 단어의 빈도나 동시출현 빈도, 이를 변형한 단어 가중치 등에 근거하여 핵심어(구)를 식별하는 수준에 그쳐있다. 이에 본 연구는 한글 학술논문의 초록으로부터 추출한 다양한 자질 요소들을 학습하여 핵심어(구)를 추출하는 모델을 제안하였고 그 성능을 평가하였다.

• Journal of the Korean Society for information Management
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• v.17 no.1
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• pp.49-65
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• 2000

The availability and use (citedness) of Korean medical journals are measured based on the bibliometric data of 82 journals evaluated by the Korean Association of Medical Journal Editors between 1997 and 1999. A Korean medical journal is held on the average by one half of Korean medical libraries investigated. Only 10 journals (12.2%) are covered in any of 36 abstract and index databases in the field of medicine searchable through DIALOG. The journal self-citation rate is 3.402%. 1.092% of papers are cited at least once by SCI journal papers within 3 years after publication. The average SCI impact factor of Korean medical journals is 0.111, However, the impact factor of MEDLINE or SCISearch journals is 10 times higher. The results show that the Korean medical journals are not easily available domestically and internationally. They are hardly cited by Korean colleagues or by foreign scholars either.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.2
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• pp.55-82
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• 2012

This study seeks to develop a curriculum operating model for Korean Library and Information Science, based on investigations into LIS curricula at home and abroad. Standard courses that can be applied to this model were also proposed. This study comprehensively analyzed the contents of domestic and foreign curricula and surveyed current librarians in all types of library fields. As a result, this study proposed required courses, core courses, and elective courses. Six required LIS courses are: Introduction to Library and Information Science, Information Organization, Information Services, Library and Information Center Management, Information Retrieval, and Field Work. Six core LIS courses are: Classification & Cataloging Practice, Subject Information Resources, Collection Development, Digital Library, Introduction to Bibliography, and Introduction to Archive Management. Twenty selective LIS courses include: the General Library and Information Science area (Cultural History of Information, Information Society and Library, Library and Copyright, Research Methods in Library and Information Science), the Information Organization area (Metadata Fundamentals, KORMARC Practice), the Information Services area (Information Literacy Instruction, Reading Guidance, Information User Study), the Library and Information Center Management area (Library Management, including management for different kinds of libraries, Library Information Cooperator, Library Marketing, Non-book Material and Multimedia Management (Contents Management), the Information Science area (Database Management, including Web DB Management, Indexing and Abstracting, Introduction to Information Science, Understanding Information Science, Automated System of Library, Library Information Network), and the Archival Science area (Preservation Management).

• Knowledge Management Research
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• v.23 no.3
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• pp.129-152
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• 2022

As a key infrastructure for digital transformation, the spread of data, network, artificial intelligence (D.N.A.) fields and the emergence of promising industries are laying the groundwork for active digital innovation throughout the economy. In this study, by applying the text mining methodology, major topics were derived by using the abstract, publication year, and research field of the study corresponding to the SCIE, SSCI, and A&HCI indexes of the WoS database as input variables. First, main keywords were identified through TF and TF-IDF analysis based on word appearance frequency, and then topic modeling was performed using g-DMR. With the advantage of the topic model that can utilize various types of variables as meta information, it was possible to properly explore the meaning beyond simply deriving a topic. According to the analysis results, topics such as business intelligence, manufacturing production systems, service value creation, telemedicine, and digital education were identified as major research topics in digital transformation. To summarize the results of topic modeling, 1) research on business intelligence has been actively conducted in all areas after COVID-19, and 2) issues such as intelligent manufacturing solutions and metaverses have emerged in the manufacturing field. It has been confirmed that the topic of production systems is receiving attention once again. Finally, 3) Although the topic itself can be viewed separately in terms of technology and service, it was found that it is undesirable to interpret it separately because a number of studies comprehensively deal with various services applied by combining the relevant technologies.