• Knowledge Management Research
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• v.5 no.1
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• pp.1-17
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• 2004

Based on the diffusion of innovation paradigm, this study conceptualizes the constituent components (3P) and the growth stages (6C) for knowledge management. It is critical for knowledge management efforts to identify 'where we are' and decide 'where to go' and then to manage 'how to go'. As a framework for the success of knowledge management, the 3P6C model is intended to systematically guide these efforts toward knowledge asset management and implementation, for knowledge productivity. This model is illustratively applied to such success stories as in Skandia, Buchman Lab and Hall Mark Cards. Such applications of this model show that they have been through such prior activities required in the earlier stages, and thattechnological platform is just one of the 3 key components working as an enabler, implying together the existence of growth path in KM success. Provided in the appendix are a set of exemplary scenarios in knowledge management practice for growth stage assessment.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.33-33
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• 1991

The management of enterprise knowledge has been increasingly important because knowledge emerges as the new basis of competition in postcapitalist society. One of the key issues in knowledge management is to put knowledge into a repository where it can be easily stored, reused, and recreated. This paper proposes a model repository and the corresponding knowledge management framework. The emphases of model repository is on abstraction knowledge in the form of schematic models. Two major benefits are model independence and model integration. A metaschema is constructed according to six conceptual components: separate unit, external link, internal link, separate unite descriptor, link descriptor, and composite descriptor, which can be applied for a variety of models. A prototype system with a case illustrates the practical usefulness of model repository for knowledge management

• Korean Management Science Review
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• v.16 no.2
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• pp.33-49
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• 1999

The management of enterprise knowledge has been increasingly important because knowledge emerges as the new basis of competition in postcapitalist society. One of the key issues in knowledge management is to put knowledge into a repository where it can be easily stored, reused, and recreated. This paper proposes a model repository and the corresponding knowledge management framework. The emphases of model repository is on abstraction knowledge in the form of schematic models. Two major benefits are model independence and model integration. A metaschema is constructed according to six conceptual components: separate unit, external link, internal link, separate unite descriptor, link descriptor, and composite descriptor, which can be applied for a variety of models. A prototype system with a case illustrates the practical usefulness of model repository for knowledge management.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.13-34
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• 1999

Building a knowledge base effectively has been an important research area in the expert systems field. A variety of approaches have been studied including rules, semantic networks, and frames to represent the knowledge base for expert systems. As the size and complexity of the knowledge base get larger and more complicated, the integration of knowledge based with database technology cecomes more important to process the large amount of data. However, relational database management systems show many limitations in handing the complicated human knowledge due to its simple two dimensional table structure. In this paper, we propose Object-Oriented Knowledge Store (OOKS), a knowledge base model on the basis of a frame sturcture using an object-oriented database. In the proposed model, managing rules for inferencing and facts about objects in one uniform structure, knowledge and data can be tightly coupled and the performance of reasoning can be improved. For building a knowledge base, a knowledge script file representing rules and facts is used and the script file is transferred into a frame structure in database systems. Specifically, designing a frame structure in the database model as it is, it can facilitate management and utilization of knowledge in expert systems. To test the appropriateness of the proposed knowledge base model, a prototype system has been developed using a commercial ODBMS called ObjectStore and C++ programming language.

• Knowledge Management Research
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• v.7 no.2
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• pp.53-68
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• 2006

Knowledge has become an important resource for organization. The manufacturing industry is usually operated on the basis of business processes, and most workers are familiar with their own processes. The process-based approach, therefore, can provide an efficient way to capture and navigate knowledge. In this study, we focus on knowledge which may be missed during knowledge transfer among workers. For this, we propose a method for analyzing knowledge flow, which is passed among business processes. We propose a process-based knowledge management framework for analyzing knowledge flow, which employs a two-phase analysis: process analysis and knowledge flow analysis. A knowledge flow model, represented by Knowledge Flow Diagram, is proposed as a tool for representing knowledge. We formulate several semantics for knowledge flow modeling. We build the three-level schema: conceptual, logical, and physical in order to automate the knowledge model adaptive to knowledge management systems. The proposed approach is verified and illustrated through a case study on the manufacturing process of A Company.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.12-12
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• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• Korean System Dynamics Review
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• v.6 no.2
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• pp.5-23
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• 2005

This paper investigates a dynamic mechanism underlying the process of knowledge creation and evolution with a focus on the SECI model(standing for Socialization, Externalization, Combination, Internalization) as proposed by Nonaka and Takeuchi(1991) and broadly accepted especially among the practitioners in knowledge management field. The SECI model provides with intuitive logic and clear delineation of knowledge types between the tacit and the explicit, and embodies an interaction dynamic. However explanations of the propelling forces for the knowledge transfer over the four quadrants of the model is yet to be made. And the transmission mechanisms are not prescribed though the model mentions knowledge is created and evolved in a spiral process. This paper, therefore attempts first to extend and elaborate it into a dynamic SECI model by identifying those propelling factors and their relationships(linkages) based on the systems thinking.

• The Journal of Society for e-Business Studies
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• v.5 no.2
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• pp.143-150
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• 2000

This paper presents a methodology how to utilize management of research scheduling plan, processing, and results using Web Knowledge Database System, which integrates research knowledge management model under the Research ＆ Development Environment. The content of this paper consists of description on utilization of the Web Knowledge Database System, sharing of the Research Knowledge through design data review, communications, and management of research knowledge flow during the Research ＆ Development Period.

• Knowledge Management Research
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• v.1 no.1
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• pp.91-107
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• 2000

This paper proposes the Organizational Knowledge Discovery Process Model (OK-DPM) as an initiative for developing a knowledge management methodology. OK-DPM is a model designed to effectively discover knowledge useful to the organization. It explains the knowledge discovery process from the conceptual level to the application level. It decomposes the organizational knowledge discovery process into 3 sub-processes; Creation, Suggestion and Validation. For each sub-process, design components are identified and possible methods for supporting each one are suggested. Also, the relationship patterns between the knowledge discovery process and knowledge type are explored. By applying OK-DPM to two real cases where the knowledge management projects are ongoing, the model was validated and revised. Even though we need to investigate with more cases to refine the OK-DPM, we found that it could provide some insights in developing the effective knowledge discovery process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1442-1453
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• 2016

Now, there are prodigiously expanding worldwide economic networks in the information society, which require their social structural changes through technology innovations. This paper so tries to formally define a process-centered knowledge model to be used to analyze policy-making procedures on technology innovations. The eventual goal of the proposed knowledge model is to apply itself to analyze a topic network based upon composite keywords from a document written in a natural language format during the technology innovation procedures. Knowledge model is created to topic network that compositing driven keyword through text mining from natural language in document. And we show that the way of analyzing knowledge model and automatically generating feature keyword and relation properties into topic networks.