• Title/Summary/Keyword: knowledge/information networks

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A Study on the Knowledge Structure Networks of International Collaboration in Psychiatry (정신의학 분야 국제공동연구의 지식구조 네트워크에 관한 연구)

  • Kim, Eun-Ju;Nam, Tae-Woo
    • Journal of the Korean Society for information Management
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    • v.32 no.3
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    • pp.317-340
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    • 2015
  • This study clarified the knowledge structure of international collaboration in psychiatry based on analyzing networks in order to construct cooperation networks for international collaboration in psychiatry in South Korea. The result of analysis of knowledge structure at a state-level is as follows. First, this study found that the rate of collaboration for five years is high as 89.97%. Moreover, this study investigated the change of rate of collaboration and international collaboration according to the passage of time, and ascertained that while the rate of international collaboration has increased, Second, this study examined the trend of research on collaboration between Asian countries, and found that collaboration between Asian countries is on a low level. Third, the country (or group) that the number of papers of international collaboration and the value of centrality are the highest is EU-28. The result of analysis of knowledge structure at a research output-level is as follows. this study analyzed the correlation of centrality with research output, and found that positive correlation exists in the three indicators of centrality, and a country with high centrality has good research output.

Knowledge Discovery Process from the Web for Effective Knowledge Creation: Application to the Stock Market (효과적인 지식창출을 위한 웹 상의 지식채굴과정 : 주식시장에의 응용)

  • Kim, Kyoung-Jae;Hong, Tae-Ho;Han, In-Goo
    • Knowledge Management Research
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    • v.1 no.1
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    • pp.81-90
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    • 2000
  • This study proposes the knowledge discovery process for the effective mining of knowledge on the web. The proposed knowledge discovery process uses the Prior knowledge base and the Prior knowledge management system to reflect tacit knowledge in addition to explicit knowledge. The prior knowledge management system constructs the prior knowledge base using a fuzzy cognitive map, and defines information to be extracted from the web. In addition, it transforms the extracted information into the form being handled in mining process. Experiments using case-based reasoning and neural network" are performed to verify the usefulness of the proposed model. The experimental results are encouraging and prove the usefulness of the proposed model.

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CoP Lead Knowledge Management - A Case of iCOOP Consumers' Co-operative - (CoP 활성화를 통한 지식경영 - 아이쿱생협의 인트라넷 활용사례-)

  • Park, Yoon Kyu;Park, Sang Sun;Jeong, Chan Yul;Kim, Dasom;Lee, Jae Hun
    • Knowledge Management Research
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    • v.14 no.5
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    • pp.35-53
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    • 2013
  • This paper aims to describe how knowledge management could be put into practice in a voluntary way. From a practice-based standpoint, this study focused closely on the linkage between knowledge and practice. It is because knowledge management could fail if not put into practice. Using its own information system, iCOOP, a federation of consumers' co-operatives in Korea has been practised successful knowledge management voluntarily with its members. Based on the exploratory case study on iCOOP, this study conducted focused interviews with 5 member co-operatives of iCOOP. Main findings are as follows. First, an NoP emerges within a corporate information system when corporate work processes are concentrated in the information system. Second, corporate information system facilitates CoPs and the NoP when its information and information about its users are opened to all of the information system users. In conclusion, this study points out that it is not the matter of primary importance to build a knowledge management system. Rather, practice has the key to the successful knowledge management.

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A Fuzzy Neural Network: Structure and Learning

  • Figueiredo, M.;Gomide, F.;Pedrycz, W.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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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.

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An Investigation on Structural Analysis of the Subject Literature Using Author Cocitation and Transition Matrix System among Subareas (저자들의 동시인용과 하위주제간 추이행렬시스템을 통한 주제문헌의 구조적 분석에 관한 고찰)

  • 김현희
    • Journal of the Korean Society for information Management
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    • v.6 no.2
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    • pp.21-44
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    • 1989
  • This study investigates author cocitation and author transition analysis which are two techniques to be used to construct author and concept networks by using a test collection of 4, 598 documents on the subject of chemistry. The author and concept networks can be used to understand the structual Knowledge of terms as well as intellectual structure of science. So, these networks could be basic data of knowledge base for subject literature.

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Rendezvous in Cognitive Radio Networks without Common Control Channel

  • Htike, Zaw;Hong, Choong-Seon
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06d
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    • pp.230-231
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    • 2011
  • In this paper, we propose a rendezvous mechanism for cognitive radio networks. In this mechanism, no prior knowledge of wireless nodes is required and it is totally distributed. Node can simply choose one of two strategies to rendezvous with its neighbors. The main benefit of this mechanism is eliminating the use of common control channel and centralized controller.

On Design Patterns for Sensor Networks

  • Amin, Syed Obaid;Hong, Choong-Seon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2007.05a
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    • pp.1535-1537
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    • 2007
  • A design pattern is a general solution to a commonly occurring problem. Design patterns have proven highly effective in representing, transferring, and applying the design knowledge in many engineering disciplines. However, these patterns have not addressed sensor network specifically. With a growth of sensors and sensor networks, and considering their profound applicability, there is a crucial need to articulate ones experience of application development or deployment of sensor nodes in the form of design patterns to avoid the future mistakes. This paper discusses the same issue and show applicability of design patterns in sensor networks.

Synergism of Knowledge-Based Decision Support Systems and Neural Networks to Design an Intelligent Strategic Planning System (지능적 전략계획시스템 설계를 위한 지식기초 의사결정지원체제와 인공신경망과의 결합)

  • Lee, Geon-Chang
    • Asia pacific journal of information systems
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    • v.2 no.1
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    • pp.35-56
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    • 1992
  • This paper proposes a synergism of neural networks (NN) and knowledge-based decision support system (KBDSS) to effectively design an intelligent strategic planning system. Since conventional KBDSS becomes inoperative partially or totally when problem deviates slightly from the expected problem-domain, a new DSS concept is needed for designing an effective strategic planning system, where strategic planning environment is usually turbulent and consistently changing. In line with this idea, this paper developes a NN-based DSS, named ConDSS, incorporating the generalization property of NN into its knowledge base. The proposed ConDSS was extensively operated in an experimentally designed environment with three models: BCG matrix, Growth/Gain matrix, and GE matrix. The results proved very promising when encountered with unforeseen situations in comparisons with conventional KBDSS.

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Performance Analysis of Hint-KD Training Approach for the Teacher-Student Framework Using Deep Residual Networks (딥 residual network를 이용한 선생-학생 프레임워크에서 힌트-KD 학습 성능 분석)

  • Bae, Ji-Hoon;Yim, Junho;Yu, Jaehak;Kim, Kwihoon;Kim, Junmo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.5
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    • pp.35-41
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    • 2017
  • In this paper, we analyze the performance of the recently introduced Hint-knowledge distillation (KD) training approach based on the teacher-student framework for knowledge distillation and knowledge transfer. As a deep neural network (DNN) considered in this paper, the deep residual network (ResNet), which is currently regarded as the latest DNN, is used for the teacher-student framework. Therefore, when implementing the Hint-KD training, we investigate the impact on the weight of KD information based on the soften factor in terms of classification accuracy using the widely used open deep learning frameworks, Caffe. As a results, it can be seen that the recognition accuracy of the student model is improved when the fixed value of the KD information is maintained rather than the gradual decrease of the KD information during training.

Applying Hebbian Theory to Enhance Search Performance in Unstructured Social-Like Peer-to-Peer Networks

  • Huang, Chester S.J.;Yang, Stephen J.H.;Su, Addison Y.S.
    • ETRI Journal
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    • v.34 no.4
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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.