• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.884-888
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• 2003

In this paper, we introduce the hybrid data mining mechanism based in association rule and fuzzy neural networks (FNN). Most of data mining mechanisms are depended in the association rule extraction algorithm. However, the basic association rule-based data mining has not the learning ability. In addition, sequential patterns of association rules could not represent the complicate fuzzy logic. To resolve these problems, we suggest the hybrid mechanism using association rule-based data mining, and fuzzy neural networks. Our hybrid data mining mechanism was consisted of four phases. First, we used general association rule mining mechanism to develop the initial rule-base. Then, in the second phase, we used the fuzzy neural networks to learn the past historical patterns embedded in the database. Third, fuzzy rule extraction algorithm was used to extract the implicit knowledge from the FNN. Fourth, we combine the association knowledge base and fuzzy rules. Our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic.

• 디지털융복합연구
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• 제11권2호
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• pp.279-285
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• 2013

정보통신망과 컴퓨터 기술의 발전은 수많은 정보 및 지식을 생산해 내는 기반이 되었고, 최근 대중화가 가속화 되고 있는 스마트디바이스는 사용자가 원하는 정보와 지식을 쉽게 획득할 수 있는 도구로 사용되고 있다. 이에 본 논문에서는 인터넷 정보와 소셜네트워크를 활용한 스마트 디바이스 기반의 지식공유 시스템을 제안한다. 제안하는 시스템은 사용자 질의에 대해 인터넷 정보 검색, 축적된 지식 검색, 소셜네트워크 상의 지인 답변 기능으로 구성된다. 제안한 시스템의 효용성 분석을 위하여 사용자 만족도 평가를 실시하였다. 실험결과 스마트디바이스를 이용한 지식공유 시스템이 일반 정보검색엔진에 비해 통계적으로 유의미한 만족도를 나타냈다.

• Journal of Contemporary Eastern Asia
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• 제13권1호
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• pp.1-4
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• 2014

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제23권4호
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• pp.329-350
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• 2019

This paper examines individual and social strategies to form profitable cooperation networks. These two types of strategies measure network stability and efficiency that may not meet in a single network. We apply restrictions on knowledge flows (R&D spillovers) and links formation to integrate these benefits into structures that ensure high outcomes for both strategies. The results suggest that linking the spillovers to the firms' positions and restricting cooperation contribute to reducing the conflict between the individual and social strategies in the development of cooperative networks.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1171-1174
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• 1993

A promising approach to get the benefits of neural networks and fuzzy logic is to combine them into an integrated system to merge the computational power of neural networks and the representation and reasoning properties of fuzzy logic. In this context, this paper presents a fuzzy neural network which is able to code fuzzy knowledge in the form of it-then rules in its structure. The network also provides an efficient structure not only to code knowledge, but also to support fuzzy reasoning and information processing. A learning scheme is also derived for a class of membership functions.

• 대한지리학회지
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• 제38권2호
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• pp.237-256
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• 2003

본 연구는 대덕밸리에 입지한 벤처기업들의 지식생산 및 상용화 과정을 산-(학)연 네트워크 차원에서 분석하고, 이를 기반으로 효율적이고 경쟁력 있는 지역혁신체제 구축방안을 제시하고자 하는데 그 목적이 있다. 1997년 이후 '제 2의 실리콘밸리' 구축을 위한 정부의 의지에 힘입어 조성된 대덕밸리는 기존의 과학연구단지를 기반으로 외형적인 혁신시스템을 갖추었다. 그럼에도 불구하고 본 연구결과 벤처기업의 지식생산과 상용화에 몇가지 근본적인 문제점이 드러났다. 이는 혁신시스템을 구성하고 있는 경제 주체들의 역할이 제 기능을 하지 못하고 있을 뿐만 아니라 혁신 주체들간의 연계를 활성화하고 조정할 수 있는 적절한 제도 및 기제의 부족에 기인한 것으로 나타났다 특히. 이와 같은 문제점은 벤처기업의 성장단계별로 그리고 지식생산 단계별로 상이하게 나타났다. 따라서 본 연구는 대덕밸리의 효율적인 지식생산 네트워크 기반의 혁신시스템 구축을 위해서 새로운 혁신시스템 구축이라는 관점보다는 기존 혁신체제를 구성하고 있는 주체 및 제도의 역할 보완 및 확충이라는 관점에서 그리고 기업의 성장단계별 및 지식생산 단계별로 몇 가지 정책적 시사점을 제시하였다.

• 대한간호학회지
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• 제41권5호
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• pp.623-632
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• 2011

Purpose: This study was done to explore the knowledge structure of Korean Nursing Science. Methods: The main variables were key words from the research papers that were presented in the Journal of Korean Academy of Nursing and journals of the seven branches of the Korean Academy of Nursing. English titles and abstracts of the papers (n=5,936) published from 1995 through 2009 were included. Noun phrases were extracted from the corpora using an in-house program (BiKE Text Analyzer), and their co-occurrence networks were generated via a cosine similarity measure, and then the networks were analyzed and visualized using Pajek, a Social Network Analysis program. Results: With the hub and authority measures, the most important research topics in Korean Nursing Science were identified. Newly emerging topics by three-year period units were observed as research trends. Conclusion: This study provides a systematic overview on the knowledge structure of Korean Nursing Science. The Social Network Analysis for this study will be useful for identifying the knowledge structure in Nursing Science.

• 지식경영연구
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• 제19권3호
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• pp.47-61
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• 2018

A knowledge map, a taxonomy of knowledge repositories, must have capabilities supporting and enhancing knowledge user's activity to search and select proper knowledge for problem-solving. Conventional knowledge maps, however, have been hierarchically categorized, and could not support such activity that must coincide with the user's cognitive process for knowledge utilization. This paper, therefore, aims to verify and develop a methodology to build a networked knowledge map that can support user's activity to search and retrieve proper knowledge based on the referential navigation between content-relevant knowledge. This paper deploys keywords as the semantic information between knowledge, because they can represent the overall contents of a given document, and because they can play the role of semantic information on the link between related documents. By aggregating links between documents, a document network can be formulated: a keyword-based networked knowledge map can be finally built. Domain expert-based validation test was also conducted on a networked knowledge map of 50 research papers, which confirmed the performance of the proposed methodology to be outstanding with respect to the precision and recall.

• ETRI Journal
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• 제30권5호
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• pp.627-633
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• 2008

The technologies for wireless communication, sensing, and computation are each progressing at faster and faster rates. Notably, they are also being combined for an amazingly large multiplicative effect. It can be envisioned that the world will eventually be covered by networks of networks of smart sensors and actuators. This fact will give rise to revolutionary applications. However, to make this vision a reality, many research challenges must be overcome. This paper describes a representative set of new applications and identifies several key research challenges.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.134-139
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• 1994

In this paper the comparison between the neural networks and traditional approaches as system identification method are considered. Two model structures of neural networks are the state space model and the input output model neural networks. The traditional methods are the AutoRegressive eXogeneous Input model and the Nonlinear AutoRegressive eXogeneous Input model. The examples considered do not represent any physical system, no a priori knowledge concerning their structure has been used in the identification process. Testing inputs for comparison are the sinusoidal, ramp and the noise ramp.