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Keyword-based networked knowledge map expressing content relevance between knowledge
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Keedong Yoo (Dept. of Business Administration, Dankook University)
Vol. 24, No. 3, Page: 119 ~ 134
10.13088/jiis.2018.24.3.119
Keywords
Knowledge map, Content relevance, Associated knowledge, Knowledge network, Keyword-based
semantic link
Abstract
A knowledge map as the taxonomy used in a knowledge repository should be structured to support and supplement knowledge activities of users who sequentially inquire and select knowledge for problem solving. The conventional knowledge map with a hierarchical structure has the advantage of systematically sorting out types and status of the knowledge to be managed, however it is not only irrelevant to knowledge user’s process of cognition and utilization, but also incapable of supporting user's activity of querying and extracting knowledge. This study suggests a methodology for constructing a networked knowledge map that can support and reinforce the referential navigation, searching and selecting related and chained knowledge in term of contents, between knowledge. Regarding a keyword as the semantic information between knowledge, this research’s networked knowledge map can be constructed by aggregating each set of knowledge links in an automated manner. Since a keyword has the meaning of representing contents of a document, documents with common keywords have a similarity in content, and therefore the keyword-based document networks plays the role of a map expressing interactions between related knowledge. In order to examine the feasibility of the proposed methodology, 50 research papers were randomly selected, and an exemplified networked knowledge map between them with content relevance was implemented using common keywords.
Show/Hide Detailed Information in Korean
지식 간 내용적 연관성을 표현하는 키워드 기반 네트워크형 지식지도 개발
유기동 (단국대학교 경영학부)
Keywords
지식지도, 내용적 연관성, 연관지식, 지식네트워크, 키워드 기반 시맨틱 링크
Abstract
저장 및 관리하는 지식의 분류체계로서의 의미를 갖는 지식지도는, 문제해결을 위하여 지식을 조회 및 선택하는 사용자의 활동을 지원하고 보완할 수 있는 구조를 갖추어야 한다. 계층형 구조를 갖는
기존의 지식지도는, 관리하는 지식을 체계적으로 정리하는 데에는 이점이 있으나, 지식 사용자가 갖는 인지 및 활용의 논리를 반영하지 못할 뿐만 아니라 지식을 조회 및 추출하는 사용자의 활동을 지원하
지 못한다. 본 연구는, 내용적 관련성을 갖는 연관지식을 연쇄적으로 조회 및 추출하는 사용자의 지식활용 패턴을 반영하는, 키워드 기반 네트워크형 지식지도를 구축하는 방법론을 제시한다. 즉, 지식 간
내용적 연관성을 파악하기 위하여 키워드를 추출하고 공통된 키워드를 갖는 지식 간 링크를 해당 키워드를 이용하여 정의한다. 키워드는 해당 지식의 내용을 대변하므로, 키워드를 기반으로 정의된 링크는
내용적으로 관련성이 있는 지식 간에 형성되며, 이를 종합하면 내용적 연관성을 지식 간의 네트워크,즉 네트워크형 지식지도가 완성된다. 제시된 방법론의 적용 타당성을 검토하기 위해 50개의 연구논문
을 이용하여 이들 간의 내용적 연관성을 표현하는 네트워크형 지식지도를 구현하였으며, 검토 결과 만족할만한 수준의 정밀도와 재현율을 보였다.
Cite this article
JIIS Style
Yoo, K., , "Keyword-based networked knowledge map expressing content relevance between knowledge", Journal of Intelligence and Information Systems, Vol. 24, No. 3 (2018), 119~134.

IEEE Style
Keedong Yoo, "Keyword-based networked knowledge map expressing content relevance between knowledge", Journal of Intelligence and Information Systems, vol. 24, no. 3, pp. 119~134, 2018.

ACM Style
Yoo, K.,, 2018. Keyword-based networked knowledge map expressing content relevance between knowledge. Journal of Intelligence and Information Systems. 24, 3, 119--134.
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@article{Yoo:JIIS:2018:740,
author = {Yoo, Keedong},
title = {Keyword-based networked knowledge map expressing content relevance between knowledge},
journal = {Journal of Intelligence and Information Systems},
issue_date = {September 2018},
volume = {24},
number = {3},
month = Sep,
year = {2018},
issn = {2288-4866},
pages = {119--134},
url = {http://dx.doi.org/10.13088/jiis.2018.24.3.119 },
doi = {10.13088/jiis.2018.24.3.119},
publisher = {Korea Intelligent Information System Society},
address = {Seoul, Republic of Korea},
keywords = { Knowledge map, Content relevance, Associated knowledge, Knowledge network and Keyword-based
semantic link },
}
%0 Journal Article
%1 740
%A Keedong Yoo
%T Keyword-based networked knowledge map expressing content relevance between knowledge
%J Journal of Intelligence and Information Systems
%@ 2288-4866
%V 24
%N 3
%P 119-134
%D 2018
%R 10.13088/jiis.2018.24.3.119
%I Korea Intelligent Information System Society