• 디지털융복합연구
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• 제10권11호
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• pp.427-432
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• 2012

본 연구는 복합저장소 구축 방법과 복합지식 프로세스 개발을 위한 기술적 방법을 제안하였다. 본 연구에서 제안한 복합지식 저장소에 저장되는 데이터 대상은 복합지식 메타데이터와 디지털 자원 모두를 포함하며, 사용목적에 따라 사용자 역할, 기능적 요소, 서비스 범주로 나눌 수 있다. 이 세 가지 요소는 저장소의 추상적 모델을 설명하는 기본적인 구성요소이다. 본 연구에서는 복합지식의 메타데이터를 2가지 요소로 구분하여 정의하였다. Component는 지식을 사용하고 생성하는 주체나 활동단위, 리소스 자체 등에 대한 속성을 나타내고, Context는 지식객체가 포함되어 있는 맥락을 나타낸다. 복합지식 프로세스 Agent는 복합지식의 분류와 등록, 검색, 패턴 정보 관리 등의 역할을 수행하고 복합지식 저장소와 사용자 사이의 데이터 흐름과 처리를 담당한다. 복합지식 프로세스 Agent는 데이터의 검색과 추출, 분산 환경에서 데이터 교환을 위한 데이터의 수집과 출력, 저장된 데이터의 추가, 변경 등이 발생한 것을 알려주는 경고, 데이터의 저장과 등록, 메타데이터 조회 후 원하는 물리적 자료를 요청하는 요청과 전달 등의 기능으로 구성하였다. 본 연구에서 개발하고자하는 추천시스템을 위한 복합지식저장소 구축은 산업 현장에서 적시에 다양한 콘텐츠를 사용자에게 제시함으로서 일과 학습이 동시에 일어날 수 있도록 하여 시의적절한 지식을 실시간 가시화함으로써 학습 생산성을 증대하는데 도움을 줄 수 있다.

• 한방재활의학과학회지
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• 제33권4호
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• pp.157-165
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• 2023

Objectives The purpose of this study was to analyze trends in traditional Chinese treatment of medial tibial stress syndrome (MTSS) and suggest directions for future research in Korea. Methods We investigated clinical studies using traditional Chinese medicine for treatment of MTSS through China National Knowledge Infrastructure search. Fourteen studies published from 2000 to 2022 were adopted and analyzed. We examined authors, type of study design, publishied year, intervention, treatment effectiveness. Results Among 14 studies, 8 were case reports and 6 were randomized controlled trials. Four interventions were used in 14 studies. Acupuncture and physical therapy were most frequently used interventions, each used in 12 studies. For evaluation of treatment effectness, 7 outcome measurements were used, effective rate was the most commonly used measurement. All of 14 studies showed good treatment results. Conclusions Through this study, we were able to identify current trends of Chinese medicine treatment for MTSS. Based on this, more study should be conducted to accumulate evidence for Korean medicine treatment of MTSS.

• International Journal of Knowledge Content Development & Technology
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• 제14권3호
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• pp.93-113
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• 2024

This study was conducted for the purpose of deriving the existing ScienceON elements and reorganizing them to increase user convenience and utilization. Towards this end, implications were derived by analyzing the current status of the ScienceON's website, case studies and analysis of major similar institution websites, and user satisfaction surveys. Based on the derived contents, key terms were analyzed and redefined, the menu system was reorganized, and the menu names were redefined, and the menu system was reorganized to match the direction and identity of the redefined ScienceON. The study results based on such are as follows. First, the ScienceON's brand selection criteria and direction were based on service sustainability, service inclusiveness, recognition of portal characteristics, user friendliness and intuitiveness. Considering the meaning of branding, branding strategy, and selection criteria for ScienceON branding, ScienceON, Ontong ScienceON, ScienceONPlatform, science information portal, ScienceON, Mecca of science and technology information, and 5 brand names such as ScienceON were proposed. Second, to improve accessibility, usability, and satisfaction, it would be necessary to redefine current terms. Towards this end, it would be necessary to change the terminology of knowledge infrastructure search and to unify and organize the terminology. Third, in the current menu, the services provided as analysis services and curation services are organized in the beta service menu, and data such as papers, patents, reports, and trends are also serviced only through integrated search, and hence, each data type and service type classification must be improved.

• 정보관리학회지
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• 제5권1호
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• pp.131-152
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• 1988

본 연구에서는 컴퓨터를 이용하는 탐색 시스템에서 탐색 용어와 관련된 제한점을 해결하고자 의미 네트워크 모델에 지식 베이스를 설계하였다. 이것은 탐색 전략에서 주제분 야의 용어 및 용어간의 어의적 관계에 대한 지식을 확장 이용하였을 때 검색의 효율을 높이 는 데에 촛점을 두었다. 이를 위해서 정보의 탐색과 지식 표현에 관한 문헌 연구를 하였으 며, 실제로 한글 문헌의 화학 공학분야에서 색인어 실험을 통하여 '유체의 흐름'과 '연소'에 관한 지식 베이스를 구성하였다. 탐색 방법은 두가지로 구분되었는데 용어에 관한 탐색과 질문식과 관련된 문헌 검색으로 실시되었다.

• ETRI Journal
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• 제34권4호
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• pp.591-601
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• 2012

Unstructured peer-to-peer (p2p) networks usually employ flooding search algorithms to locate resources. However, these algorithms often require a large storage overhead or generate massive network traffic. To address this issue, previous researchers explored the possibility of building efficient p2p networks by clustering peers into communities based on their social relationships, creating social-like p2p networks. This study proposes a social relationship p2p network that uses a measure based on Hebbian theory to create a social relation weight. The contribution of the study is twofold. First, using the social relation weight, the query peer stores and searches for the appropriate response peers in social-like p2p networks. Second, this study designs a novel knowledge index mechanism that dynamically adapts social relationship p2p networks. The results show that the proposed social relationship p2p network improves search performance significantly, compared with existing approaches.

• International Journal of Contents
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• 제8권1호
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• pp.100-107
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• 2012

While considerable research suggests that users' uncertainty gradually decreases, as they proceed through the information seeking process, others argue that it can arise at any stage of their information seeking process. Reflecting the latter view, this study examined user perceptions of uncertainty in the final stage of users' information seeking process, the stage of search results evaluation. Considering the significance of Web search engines for academic study, this study investigated the relevance decision stage of scholarly researchers in the field of science, who use Web search engines for their academic study. Based on the analysis of the users' uncertainty, this study provided implications to improve information systems and Web contents design.

• Interdisciplinary Bio Central
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• 제3권3호
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• pp.9.1-9.5
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• 2011

Entity Attribute Value (EAV) is the widely used solution to represent high dimensional and sparse data, but EAV is not search efficient for knowledge extraction. In this paper, we have proposed a search efficient data model: Optimized Entity Attribute Value (OEAV) for physical representation of high dimensional and sparse data as an alternative of widely used EAV. We have implemented both EAV and OEAV models in a data warehousing en-vironment and performed different relational and warehouse queries on both the models. The experimental results show that OEAV is dramatically search efficient and occupy less storage space compared to EAV.

• 한국정보과학회논문지:시스템및이론
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• 제33권7호
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• pp.448-453
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• 2006

본 논문은 평면 그래프를 위한 병렬 depth-first search (DFS) 알고리즘 [SIAM J. Comput., 19 (1990) 678-704]을 비 평면일 (non-planar) 수 있는 grid 그래프의 한 종류인 solid grid 그래프에 대해서도 수행 가능하도록 확장된 알고리즘을 제안한다. 제안 알고리즘은 Priority PRAM 모델에서 $O(n/sqrt{log\;n})$개의 프로세서로 수행했을 때 O(log n)의 병렬 시간이 소요된다. 우리의 지식으로, 이는 비 평면 그래프를 위한 첫 번째 결정적 NC (deterministic NC) 알고리즘이다.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2000년도 추계공동학술대회논문집
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• pp.375-389
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• 2000

Fuzzy logic ignores some information in the reasoning process. Neural networks are powerful tools for the pattern processing, but, not appropriate for the logical reasoning. To model human knowledge, besides pattern processing capability, the logical reasoning capability is equally important. Another new neural network called neural logic network is able to do the logical reasoning. Because the fuzzy inference is a fuzzy logical reasoning, we construct fuzzy inference network based on the neural logic network, extending the existing rule- inference. network. And the traditional propagation rule is modified. For the search strategies to find out the belief value of a conclusion in the fuzzy inference network, we conduct a simulation to evaluate the search costs for searching sequentially and searching by means of search priorities.

• 한국CDE학회논문집
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• 제6권4호
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• pp.229-235
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• 2001

As the networks (i.e., intranet and internet) proliferate all over the world, it is inevitable to move some (or all) of the enterprise activities into virtual spaces. Differently from business data, product data have complex semantics and thus are not properly exchanged among different application programs. Even though some neutral formats of product data have been developed by standard organizations, exchanging them among various application programs still needs the comprehensive understanding of the complex semantics. Recently, it is widely recognized that capturing more knowledge is the next step to overcome the current difficulties on sharing product data. In this paper, we utilize the ontology concept in order to facilitate information search far product data in the internet environment. A prototype of search system implemented using the ontology for automobile product data is presented.