• Title/Summary/Keyword: Terminology SNA

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Analyzing Disaster Response Terminologies by Text Mining and Social Network Analysis (텍스트 마이닝과 소셜 네트워크 분석을 이용한 재난대응 용어분석)

  • Kang, Seong Kyung;Yu, Hwan;Lee, Young Jai
    • Information Systems Review
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    • v.18 no.1
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    • pp.141-155
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    • 2016
  • This study identified terminologies related to the proximity and frequency of disaster by social network analysis (SNA) and text mining, and then expressed the outcome into a mind map. The termdocument matrix of text mining was utilized for the terminology proximity analysis, and the SNA closeness centrality was calculated to organically express the relationship of the terminologies through a mind map. By analyzing terminology proximity and selecting disaster response-related terminologies, this study identified the closest field among all the disaster response fields to disaster response and the core terms in each disaster response field. This disaster response terminology analysis could be utilized in future core term-based terminology standardization, disaster-related knowledge accumulation and research, and application of various response scenario compositions, among others.

Building and Analysis of Semantic Network on S&T Multilingual Terminology (과학기술 전문용어의 다국어 의미망 생성과 분석)

  • Jeong, Do-Heon;Choi, Hee-Yoon
    • Journal of Information Management
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    • v.37 no.4
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    • pp.25-47
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    • 2006
  • A terminology system capable of providing interpretations and classification information on a multilingual science and technology(S&T) terminology is essential to establish an integrated search environment for multilingual S&T information systems. This paper aims to build a base system to manage an integrated information system for multilingual S&T terminology search. It introduces a method to build a search system for S&T terminologies internally linked through the multilingual semantic network and a search technique on the multiple linked nodes. In order to provide a foundation for further analysis researches, it also attempts to suggest a basic approach to interpret terminology clusters generated with those two search methods.