• Title/Summary/Keyword: 내용 검색기반 전자원문

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The Enhanced Electronic Book System Based in Contents Search (내용검색기반의 전자원문 고도화를 위한 방안)

  • Jung, Ee-Sop;Yoo, Jae-Young;Cho, Hyun-Yang;Nam, Yeong-Joon
    • Proceedings of the Korean Society for Information Management Conference
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    • 2005.08a
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    • pp.311-318
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    • 2005
  • 본 논문은 e-book으로 명명된 전자 원문자료(전자책)를 구조화하여 이용자 편의성을 극대화하는 방안을 연구하였다. 대상으로 특정 컨텐트(텍스트, 이미지, 아이콘 등)를 선택하는 경우 관련정보를 웹브라우저에 의해 웹사이트에서 제공할 수 있는 내용검색기반의 전자원문 고도화 방안 연구를 목적으로 하고 있다. 연구결과 전자원문 서비스체계, 전문정보(專門情報)의 분류체계 적용, 검색효율성 및 편리성을 증진시킨 인터페이스 등의 결과를 부품소재정보망(MCT-net)에 적용하였다. 또한 전자원문의 자동구축방안, 다양한 검색기능 강화방안, 효율적인 전자원문 관리방안을 모색하였다

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A Study on the Advanced Electronic Book System Based in Web (웹기반의 전자원문 관리 시스템에 관한 연구)

  • Nam, Young-Joon;Jeong, Eui-Seob;Yoo, Jae-Young;Cho, Hyun-Yang
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.16 no.2
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    • pp.139-156
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    • 2005
  • In this paper, we design and implement electronic book system providing web-based interface for the ebook. The aim of this study is to optimize the effective reading and management of electronic text for its users(readers and librarians). Advanced functions of the electronic book system are the following: 1) Electronic book system is not dependent to specific software and tool. 2) Electronic book system is able to. minimize images(table, image, icon etc) to improve the meaning and readability of information. 3) Electronic book system is able to reduce the effort for indexing extraction and constructing the table of content. 4) The system is able to collect the user log files that are created during the process of reading ebook from various points of view. 5) When reading, the system uses the DRM through decoding and encoding the ebook.

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A Study on De Navigation Tools for Electronic Documents Based on Cognitive Process (인지과정을 고려한 전자문헌의 내비게이션 도구에 관한 고찰)

  • Lee, Byeong-Ki
    • Journal of Information Management
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    • v.30 no.1
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    • pp.48-67
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    • 1999
  • In an advanced computer and information network technologies, users are rapidly approaching environment in which information will be created, delivered, managed and stored, using vastly different methods to traditional pap r based systems. Information seeking behavior contains not only physical access, but also cognitive process in which reading, viewing, analyzing, reasoning etc. The most Important factor determining the usability of electronic documents is cognitive process. But, currently Navigation tools for using electronic documents depend on physical searching without considering cognitive process. Therefore, this study examined feasibility of using overal cognitive process in developing navigation tools. Six cognitive process style have been analyzed to find common skill of information seeking process. Also this study suggests skills that needs to introduce to functions of navigation tool, such as searching, filtering, visualization, traversal, content structure.

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Trends Analysis on Research Articles of the Sharing Economy through a Meta Study Based on Big Data Analytics (빅데이터 분석 기반의 메타스터디를 통해 본 공유경제에 대한 학술연구 동향 분석)

  • Kim, Ki-youn
    • Journal of Internet Computing and Services
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    • v.21 no.4
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    • pp.97-107
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    • 2020
  • This study aims to conduct a comprehensive meta-study from the perspective of content analysis to explore trends in Korean academic research on the sharing economy by using the big data analytics. Comprehensive meta-analysis methodology can examine the entire set of research results historically and wholly to illuminate the tendency or properties of the overall research trend. Academic research related to the sharing economy first appeared in the year in which Professor Lawrence Lessig introduced the concept of the sharing economy to the world in 2008, but research began in earnest in 2013. In particular, between 2006 and 2008, research improved dramatically. In order to grasp the overall flow of domestic academic research of trends, 8 years of papers from 2013 to the present have been selected as target analysis papers, focusing on titles, keywords, and abstracts using database of electronic journals. Big data analysis was performed in the order of cleaning, analysis, and visualization of the collected data to derive research trends and insights by year and type of literature. We used Python3.7 and Textom analysis tools for data preprocessing, text mining, and metrics frequency analysis for key word extraction, and N-gram chart, centrality and social network analysis and CONCOR clustering visualization based on UCINET6/NetDraw, Textom program, the keywords clustered into 8 groups were used to derive the typologies of each research trend. The outcomes of this study will provide useful theoretical insights and guideline to future studies.