• 제목/요약/키워드: Knowledge map

검색결과 473건 처리시간 0.032초

특허맵과 AHP를 활용한 최적의 LCD 저온폴리실리콘 결정화 기술 선정 (Determining an Optimal Low Temperature Polycrystalline Silicon Crystallization Technology of LCD using Patent Map and AHP)

  • 김관열;이장희
    • 지식경영연구
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    • 제12권1호
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    • pp.39-52
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    • 2011
  • Many LCD manufacturers continue to develop the technologies of LCD manufacturing processes for the reduction of production cost, power consumption and high-resolution. The LTPS (Low Temperature Polycrystalline Silicon) crystallization technology is important for rearranging the internal structure of liquid crystal grain by adding certain energy to amorphous silicon and turning it into poly-silicon in order to manufacture LCD with better performance. We consider 14 existing technologies of LTPS crystallization in the LCD manufacturing and present an intelligent analysis methodology using patent map and AHP (Analytic Hierarchy Process) analysis for determining an optimal LTPS crystallization technology. By using patent map analysis, we easily understand the development process and mega-trend of LTPS crystallization technologies and their relationship. By using AHP analysis, we evaluate 14 LTPS technologies. Through the use of proposed methodology, we determine the Continuous Wave Laser Lateral Crystallization technology as an optimal one.

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온톨로지 기반의 주제-객체관계를 이용한 국가 R&D 지식맵 구축 (Development of a National R&D Knowledge Map Using the Subject-Object Relation based on Ontology)

  • 양명석;강남규;김윤정;최광남;김영국
    • 정보관리학회지
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    • 제29권4호
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    • pp.123-142
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    • 2012
  • 최근 효과적인 정보검색을 제공하기 위해 시맨틱 웹을 비롯한 다양한 검색기법들을 사용하고 있다. 이중에서 효과적인 방법은 온톨로지를 이용한 검색기술을 적용하는 것이라 할 수 있다. 본 논문에서는 국가과학기술지식정보서비스(NTIS)에서 구축한 국가R&D정보를 분석하여 온톨로지를 구축하고, 이용자가 관심있어 하는 주제분야(과제, 인물, 성과, 기관)를 중심으로 온톨로지의 객체관계를 표현하고 정보를 탐색하기 위한 국가R&D지식맵(knowledge map)을 구축하였다. 국가R&D지식맵은 사용자가 선택한 객체를 중심노드로 설정하여, 주제분야를 노드로 표현하고, 객체와 주제분야간의 관계를 분석하여 사용자가 관심 있어 하는 질의를 주제분야의 하위노드로 표현하였다. 사용자가 하위노드의 질의를 선택하면 시스템에서는 선택한 질의를 온톨로지로부터 추론할 수 있는 SPAQL 질의어를 생성하고 추론엔진으로부터 검색결과를 받아 사용자에게 제시하였다.

컴퓨터공학 분야 학술 논문 데이터베이스를 이용한 키워드 연관 네트워크 기반 지식지도 (A Knowledge Map Based on a Keyword-Relation Network by Using a Research Paper Database in the Computer Engineering Field)

  • 정보석;권영근;곽승진
    • 정보처리학회논문지D
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    • 제18D권6호
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    • pp.501-508
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    • 2011
  • 최근 여러 분야에서 활용되고 있는 지식지도는 대량의 정보 속에 숨겨진 특징을 찾아서 그 의미를 파악할 수 있도록 가시적인 형태의 결과를 보여주는 것을 말한다. 본 논문에서는 2000년부터 2010년까지 컴퓨터 공학 분야의 국내 학술지에 게재된 논문들의 데이터베이스를 활용하여 연구동향 분석을 위한 키워드 연관 네트워크 기반의 지식지도를 제안하였다. 그 지식지도를 통해 키워드 연관 네트워크에서 개별 키워드가 속한 연결 요소의 크기 변화를 살펴봄으로써 관련 연구 주제의 영향력 변화를 추론할 수 있었다. 또한, 랜덤 네트워크와의 비교를 통해 키워드 연관 네트워크에서 최대 연결 요소의 크기가 상대적으로 매우 작으며, 상호 관련성이 높은 키워드 쌍들의 그룹이 밀집되어 있음을 보였다. 이는 최대 연결 요소에 대응하는 연구 분야가 크지 않으며 여러 소규모의 연구 주제들이 느슨한 형태로 연결되어 있음을 암시한다. 이러한 분석 결과들은 단순히 개별 키워드의 사용 빈도수 등을 분석하는 전통적인 방식으로는 얻기 어렵다는 점에서 본 논문에서 제안한 지식지도가 연구동향 분석의 방법이 될 수 있다.

Digital Maps and Automatic Narratives for the Interactive Global Histories

  • CHEONG, Siew Ann;NANETTI, Andrea;FHILIPPOV, Mikhail
    • Asian review of World Histories
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    • 제4권1호
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    • pp.83-123
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    • 2016
  • We describe a vision of historical analysis at the world scale, through the digital assembly of historical sources into a cloud-based database, where machine-learning techniques can be used to summarize the database into a time-integrated actor-to-actor complex network. Using this time-integrated network as a template, we then apply the method of automatic narratives to discover key actors ('who'), key events ('what'), key periods ('when'), key locations ('where'), key motives ('why'), and key actions ('how') that can be presented as hypotheses to world historians. We show two test cases on how this method works. To accelerate the pace of knowledge discovery and verification, we describe how historians would interact with these automatic narratives through an online, map-based knowledge aggregator that learns how scholars filter information, and eventually takes over this function to free historians from the more important tasks of verification, and stitching together coherent storylines. Ultimately, multiple coherent storylines that are not necessary compatible with each other can be discovered through human-computer interactions by the map-based knowledge aggregator.

웹 사이트 플로우(Flow) 측정 방법론 및 시뮬레이션에 대한 연구 (The Measuring Method of Web-Site Flow and Its Simulation Analysis)

  • 권순재
    • 지식경영연구
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    • 제10권2호
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    • pp.49-63
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    • 2009
  • In this study, sub domain of flow was investigated on literature survey, and suggested of the measuring method of web-site flow and its simulation analysis. Constructing of measuring method of flow, and using this method what-if analysis was simulated when several condition changed. Using causal map approach to extract knowledge from web-site domain experts and to derives a causal relationship of knowledge. Specially, in our study, describes method of developing and building causal map, and suggests guide line of this method on practical application. This research results show that web-site flow starts "direct searching" or "interesting of special issue(domain)", and when challenges of web-site were accorded with user's skills web-site flow grows. Further, in the web-site, information searching intention results in increase of user's duration time and experience flow to discovery new interesting issues in this process. If user's web-site of interaction is increased, awareness of environment conditions decreased, finally, user's telepresense results in increased web-site flow. This paper contained thai this method make used of measuring flow in the web-site and developing of practical strategy.

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SOM을 이용한 복합지식의 3D 가시화 방법 (3D Visualization of Compound Knowledge using SOM(Self-Organizing Map))

  • 김귀정;한정수
    • 한국콘텐츠학회논문지
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    • 제11권5호
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    • pp.50-56
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    • 2011
  • 본 연구는 복합지식 객체를 기반으로 다차원적인 관계를 쉽게 식별하고 검색할 수 있도록 복합지식의 3D 가시화방법을 제안한다. 이를 위해 복합지식을 네트워크 형태의 의미화된 링크와 노드로 구조화하고 3차원 형태로 보여줄 수 있도록 SOM을 이용한 가시화방법을 제안하였다. 또한, 3D 공간상에서 복합지식을 배치하고 사용자에게 제공함으로써 보다 실감적이고 직관적인 정보검색의 기회를 제공하기 위해서 객체 유사도를 이용한 복합지식의 3D 클러스터링 방법을 제안하였다. SOM을 이용한 복합지식의 3D 가시화와 클러스터링은 복합지식의 맥락과 연계성을 시공간에 가시화하는데 최적의 방법이 될 수 있다.

민선4기 지방자치단체 정부조직의 지식관리 전략에 관한 연구 (Note on Strategies of Knowledge Management in Government Organizations during the period of the 4th elected Local Government)

  • 강황선
    • 한국디지털정책학회:학술대회논문집
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    • 한국디지털정책학회 2006년도 춘계학술대회
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    • pp.225-233
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    • 2006
  • This note attempts to present knowledge management strategies for the upcoming 4th elected local government. Despite the series of efforts by the central government of Korea, it seems that local governments and their affiliated organizations have been very slow even understanding the necessities of knowledge management as well as adopting any particular knowledge management system. This study analyzes the evolutionary process of knowledge management policies by the central government and presents knowledge management strategies.

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A Study on the Development of Robust Fault Diagnostic System Based on Neuro-Fuzzy Scheme

  • Kim, Sung-Ho;Lee, S-Sang-Yoon
    • Transactions on Control, Automation and Systems Engineering
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    • 제1권1호
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    • pp.54-61
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    • 1999
  • FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. By using the FCM, authors have proposed FCM-based fault diagnostic algorithm. However, it can offer multiple interpretations for a single fault. In process engineering, as experience accumulated, some form of quantitative process knowledge is available. If this information can be integrated into the FCM-based fault diagnosis, the diagnostic resolution can be further improved. The purpose of this paper is to propose an enhanced FCM-based fault diagnostic scheme. Firstly, the membership function of fuzzy set theory is used to integrate quantitative knowledge into the FCM-based diagnostic scheme. Secondly, modified TAM recall procedure is proposed. Considering that the integration of quantitative knowledge into FCM-based diagnosis requires a great deal of engineering efforts, thirdly, an automated procedure for fusing the quantitative knowledge into FCM-based diagnosis is proposed by utilizing self-learning feature of neural network. Finally, the proposed diagnostic scheme has been tested by simulation on the two-tank system.

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Early Childhood Teachers' Content Knowledge on Green Growth Education

  • Yang, Jea Min;Kim, Sang Lim
    • International Journal of Advanced Culture Technology
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    • 제7권1호
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    • pp.143-149
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    • 2019
  • The purpose of the study was to examine early childhood teachers' content knowledge on green growth education. The subjects, 45 early childhood teachers, were asked to draw concept maps about early childhood green growth education. Their concept maps were analyzed in terms of superordinate and subordinate concepts by contents and frequencies. The results showed that early childhood teachers used 182 superordinate and 1,292 subordinate concepts in the concept map of green growth education for young children. Although early childhood teachers had a wealth of content knowledge on green growth education as proposed by the Ministry of Education, their knowledge was disproportionate to some areas and sub-areas of green growth education. These results implied the needs of developing teacher education programs for early childhood green growth education.

사회네트워크 분석을 활용한 비즈니스 모델 지식구조 분석 (A study of business model research knowledge structure based on social network analysis)

  • 류재홍;최진호
    • 지식경영연구
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    • 제19권2호
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    • pp.47-68
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    • 2018
  • Business environment is shifting from industrial economy to knowledge based economy. Enterprises go through numerous trials for successful management in changing environment. Along with trial tests, research area has been growing simultaneously. Unlike initial research which focused on basic concepts such as: form of business model and success points. Current research emphasizes on actualization of business that enterprises plan, which brought academic research with perplex form of knowledge structure. On the other hand, there is limitation in understanding business model systematically due to preceding research primarily centered on analyzing definition and case study. In order to analyze knowledge structure, this study utilized social network analysis based on "relationship". For the analysis, 13,412 keywords were extracted from 36years worth of article or research related to business model stored in SCOPUS database. From the analysis, it was shown core research subject was INNOVATION and the number of co-authors has increased due to the academic diversity. Business model research is divided into five sub-categories (E-commerce, SMEs, sustainability, open-source, and e-book). Through cognitive map analysis on each of research characteristics of sub-category, it has shown that E-commerce, SMEs, sustainability, and open-source are core categories.