• Title/Summary/Keyword: Automated Subject Indexing

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A One-Size-Fits-All Indexing Method Does Not Exist: Automatic Selection Based on Meta-Learning

  • Jimeno-Yepes, Antonio;Mork, James G.;Demner-Fushman, Dina;Aronson, Alan R.
    • Journal of Computing Science and Engineering
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    • v.6 no.2
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    • pp.151-160
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    • 2012
  • We present a methodology that automatically selects indexing algorithms for each heading in Medical Subject Headings (MeSH), National Library of Medicine's vocabulary for indexing MEDLINE. While manually comparing indexing methods is manageable with a limited number of MeSH headings, a large number of them make automation of this selection desirable. Results show that this process can be automated, based on previously indexed MEDLINE citations. We find that AdaBoostM1 is better suited to index a group of MeSH hedings named Check Tags, and helps improve the micro F-measure from 0.5385 to 0.7157, and the macro F-measure from 0.4123 to 0.5387 (both p < 0.01).

Index Ontology Repository for Video Contents (비디오 콘텐츠를 위한 색인 온톨로지 저장소)

  • Hwang, Woo-Yeon;Yang, Jung-Jin
    • Journal of Korea Multimedia Society
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    • v.12 no.10
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    • pp.1499-1507
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    • 2009
  • With the abundance of digital contents, the necessity of precise indexing technology is consistently required. To meet these requirements, the intelligent software entity needs to be the subject of information retrieval and the interoperability among intelligent entities including human must be supported. In this paper, we analyze the unifying framework for multi-modality indexing that Snoek and Worring proposed. Our work investigates the method of improving the authenticity of indexing information in contents-based automated indexing techniques. It supports the creation and control of abstracted high-level indexing information through ontological concepts of Semantic Web skills. Moreover, it attempts to present the fundamental model that allows interoperability between human and machine and between machine and machine. The memory-residence model of processing ontology is inappropriate in order to take-in an enormous amount of indexing information. The use of ontology repository and inference engine is required for consistent retrieval and reasoning of logically expressed knowledge. Our work presents an experiment for storing and retrieving the designed knowledge by using the Minerva ontology repository, which demonstrates satisfied techniques and efficient requirements. At last, the efficient indexing possibility with related research is also considered.

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A Study on Automatic Classification of Subject Headings Using BERT Model (BERT 모형을 이용한 주제명 자동 분류 연구)

  • Yong-Gu Lee
    • Journal of the Korean Society for Library and Information Science
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    • v.57 no.2
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    • pp.435-452
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    • 2023
  • This study experimented with automatic classification of subject headings using BERT-based transfer learning model, and analyzed its performance. This study analyzed the classification performance according to the main class of KDC classification and the category type of subject headings. Six datasets were constructed from Korean national bibliographies based on the frequency of the assignments of subject headings, and titles were used as classification features. As a result, classification performance showed values of 0.6059 and 0.5626 on the micro F1 and macro F1 score, respectively, in the dataset (1,539,076 records) containing 3,506 subject headings. In addition, classification performance by the main class of KDC classification showed good performance in the class General works, Natural science, Technology and Language, and low performance in Religion and Arts. As for the performance by the category type of the subject headings, the categories of plant, legal name and product name showed high performance, whereas national treasure/treasure category showed low performance. In a large dataset, the ratio of subject headings that cannot be assigned increases, resulting in a decrease in final performance, and improvement is needed to increase classification performance for low-frequency subject headings.

Emergency Medical System based on GIS (GIS(Geographic Information System ) 을 이용한 응급의료 진료관리 시스템 개발)

  • 이태식;구지희
    • Spatial Information Research
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    • v.4 no.1
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    • pp.43-54
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    • 1996
  • The purpose of this study is to provide GIS application to the emergency medical service management system in the Seoul area. Two wards, Kangnam-Gu and Songpa-Gu, were selected for a pilot study subject. The main focus of the study was to develope the network system using GIS which could select the most available hospital from the site being emergency case and advise the minimum path to the hospital. ARC/INFO pc version was need to implemeni an indexing system for automated mapping and data storage. The developed system, "Emergency Medical System based on GIS ${\ulcorner}$EMS/GIS${\lrcorner}m$", consists of the cartographic database and vehicle transportation system. The results suggest that EMS/GIS network are needed to connect the local transportation network between major emergency care hospitals and central conirol tower in the near future. If the EMS/GIS system could be more developed based in further analysis, it would be the most useful economical and efficient for emergency medical service with mutual aid system.al aid system.

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A Study of the Curriculum Operating Model and Standard Courses for Library & Information Science in Korea (한국문헌정보학 교과과정 운영모형 및 표준교과목 개발에 관한 연구)

  • Noh, Young-Hee;Ahn, in-Ja;Choi, Sang-Ki
    • 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).