• Journal of Information Technology Services
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• v.6 no.1
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• pp.1-15
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• 2007

An objective and valid knowledge activity indicator (KAI) is essential for encouraging knowledge activity in public institution. However, knowledge activity of public institution is inherently different from one of private corporation and, therefore, new method to find aggregated knowledge mileage considering public organizational culture and structure is to be developed. Therefore, this paper shows how to develop KAI of public institution based on three steps. First, knowledge activities were categorized as knowledge creation, knowledge sharing, and knowledge value increasing. Several knowledge indicators and hierarchical knowledge structure were developed for each knowledge categories. Second, personal knowledge mileage was calculated using AHP method considering whole organization's opinion. Finally, these approaches to find KAI were applied to "P" public institution as case studies. The results shows that KAI developed in this paper was very effective in grouping knowledge workers based on knowledge activities.

• Journal of Mechanical Science and Technology
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• v.20 no.11
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• pp.1863-1872
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• 2006

In FMS (Flexible Manufacturing System) and CIM (Computer Integrated Manufacturing), machine-tools have been the target of integration in the last three decades. The conventional concept of integration is being changed into the autonomous manufacturing device based on the knowledge evolution by applying advanced information technology in which an open architecture controller, high-speed network and internet technology are included. In the advanced environment, the machine-tools is not the target of integration anymore, but has been the key subject of cooperation. In the near future, machine-tools will be more improved in the form of a knowledge-evolutionary intelligent device. The final goal of this study is to develop an intelligent machine having knowledge-evolution capability and a management system based on internet operability. The knowledge-evolutionary intelligent machine-tools is expected to gather knowledge autonomically, by producing knowledge, understanding knowledge, reasoning knowledge, making a new decision, dialoguing with other machines, etc. The concept of the knowledge-evolutionary intelligent machine is originated from the machine control being operated by human experts' sense, dialogue and decision. The structure of knowledge evolution in M2M (Machine to Machine) and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, with intent to develop the knowledge-evolutionary machine-tools. The dialogue agent functions as an interface for inter-machine cooperation. To design the dialogue agent module in an M2M environment, FIPA (Foundation of Intelligent Physical Agent) standard platform and the ping agent based on FIPA are analyzed in this study. In addition, the dialogue agent is designed and applied to recommend cutting conditions and thermal error compensation in a tapping machine. The knowledge-evolutionary machine-tools are expected easily implemented on the basis of this study and shows a good assistance to sensory and decision support agents.

• International Commerce and Information Review
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• v.8 no.3
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• pp.3-21
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• 2006

This study aims to explore the developing strategies of knowledge based industry in ChunChon Area. This study suggests several strategies for promoting local development in Chunchon Area as follows ; first, building of local innovation system in chunchon area and convergence and diffusion of knowledge based industries. second, making of industrial environment suitable to developing knowledge based industries. third, the establishment of overall industrial supporting systems. fourth, expansion of industrial infra and prevention of the brain drain. fifth, transformation of industrial complex into innovation clusters. The result of this study will be useful for the chief executives officers to make more rational decision making for industrial developing strategies is related to the Knowledge based Industries. The paper also strives to provoke debate in this area with to encouraging further research on the topic.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.95-109
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• 2022

A blockchain based platform can ensure data integrity, reliability, and security by applying distributed processing and encryption technology for transaction records. In the existing knowledge sharing platform, the created knowledge could not be shared or utilized sufficiently due to information asymmetry and centralization. However little research has been done so far on this area. In this study, we will examine case studies and development potentials for blockchain based knowledge sharing platforms based on previous studies of blockchain technology, token economy, knowledge sharing, motivation theory, and social exchange theory. Blockchain based platforms can contribute to the activation of knowledge sharing, by resolving information asymmetry, simplifying unnecessary work procedures through unified knowledge sharing flow and excluded centralization of authority by decentralization, and strengthening access and utilization of the knowledge produced by the platform.

• Management & Information Systems Review
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• v.35 no.2
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• pp.119-136
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• 2016

The purpose of this study are as follows : First, This study conceptually provide an insight of reasons that organizations seek to create, acquire, store and distribute knowledge at the level of an organization and of process how they can transform or evolve to knowledge based organizations. Second, this study confirms examine what theories can be used to knowledge management, how such theories can be useful to analyse knowledge management and provide a theoretical foundation for knowledge management research. Applied to the theories of knowledge based and resource based view and institutional theory, the essence of knowledge management confirms that the organization finds job-related knowledge and know-how retained by individual of organizational members systematically and shares common knowledge within the organization and explains knowledge creation, multi-dimensional knowledge transition and share in all dimension of individual, group, and organization. As a result of comparative analysis of theory of organizational knowledge creation theory, In knowledge management, building of knowledge-creative culture, transitional process of explicit knowledge and tacit knowledge, knowledge creation and knowledge operation are important. In the basis on these study results, we discussed how the organizational knowledge creation theory can be used to manage knowledge in the organization, and also proposed hypotheses based on some arguments against the universal acceptance of the theory.

• 연구논문집
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• s.34
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• pp.113-119
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• 2004

Recently, the conventional concept of a machine-tool in manufacturing systems is changing from the target of integration to the autonomous manufacturing device based on a knowledge evolution. Subsequently, a machine-tool has been the subject of a cooperation through an advanced environment where an open architecture controller, high speed network and internet technology are contained In the future, a machine-tool will be more improved in the form of a knowledge evolution based device. In order to develop the knowledge evolution based machine-tool, this paper proposes the structure of knowledge evolution and the scheme of a dialogue agent among agent-based modules such as a sensory module, a dialogue module, and an expert system. The dialogue agent has a role of interfacing with another machine for cooperation. To design of the dialogue agent module in M2M(Machine To Machine)environment, FIPA-OS and ping agent based on FIPA-OS are analyzed in this study. Through this, it is expected that the dialogue agent module can be more efficiently designed and the knowledge evolution based machine-tool can be hereafter more easily implemented.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.764-770
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• 2004

This paper presents a hybrid data mining mechanism to extract expert knowledge from historical data and extend expert systems' reasoning capabilities by using fuzzy neural network (FNN)-based learning & rule extraction algorithm. Our hybrid data mining mechanism is based on association rule extraction mechanism, FNN learning and fuzzy rule extraction algorithm. Most of traditional data mining mechanisms are depended ()n association rule extraction algorithm. However, the basic association rule-based data mining systems has not the learning ability. Therefore, there is a problem to extend the knowledge base adaptively. In addition, sequential patterns of association rules can`t represent the complicate fuzzy logic in real-world. To resolve these problems, we suggest the hybrid data mining mechanism based on association rule-based data mining, FNN learning and fuzzy rule extraction algorithm. Our hybrid data mining mechanism is consisted of four phases. First, we use general association rule mining mechanism to develop an initial rule base. Then, in the second phase, we adopt the FNN learning algorithm to extract the hidden relationships or patterns embedded in the historical data. Third, after the learning of FNN, the fuzzy rule extraction algorithm will be used to extract the implicit knowledge from the FNN. Fourth, we will combine the association rules (initial rule base) and fuzzy rules. Implementation results show that the hybrid data mining mechanism can reflect both association rule-based knowledge extraction and FNN-based knowledge extension.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.5
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• pp.338-344
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• 2014

As the role of information collection becomes increasingly important in the enormous data environment, there is growing demand for more intelligent information technologies for managing complex data. On the other hand, it is difficult to find a solution because of the data complexity and big scaled amount. Accordingly, there is a need for a special intelligent knowledge base frame that can be operated by itself flexibly. In this paper, by adopting switching function for signal transmission in the synapse of the human brain, I/E selective activation based knowledge reconfiguring mechanism is proposed for building more intelligent information management system. In particular, knowledge network design, a special knowledge node structure, Type definition, I/E gauge definition and I/E matching scheme are provided. Using these concepts, the proposed system makes the functions of activation by I/E Gauge, selection and reconfiguration. In a more efficient manner, the routing and reasoning process was performed based on the knowledge reconfiguration network. In the experiments, the process of selection by I/E matching, knowledge reconfiguration and routing & reasoning results are described.

• Knowledge Management Research
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• v.9 no.3
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• pp.43-57
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• 2008

This study examines the impact of knowledge processes (KP) on the performance of knowledge management systems (KMS). It posits that task needs and available functionality of technology existing in an organization could influence the usability of KP and the KMS performance. A firm-level structural model was developed based on data collected from corporate KM users. Survey-based research was carried out to test this model. Following questionnaire development, validation, and pretest with a pilot study, data were collected from 886 knowledge management (KM) users including directors, managers, and workers in a South Korea-based company, Korea Asset Management Corporation (KAMCO), to measure the task needs and available functionality of technology to improve the KMS performance. Results show that the matching between the two factors-technology and task-had a significant influence on the usability of KP and the KMS performance, and a better usability of KP has positive impact on the KMS performance. Implications on KM practices and KMS designs are also discussed.

• Knowledge Management Research
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• v.11 no.2
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• pp.133-152
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• 2010

This paper suggests a typology of the modes of collaboration for scientific and technological knowledge production and sharing (STKPS) based on knowledge communication types, including organizational factors, communication channel, intensity, and decision-making, that affect STKPS processes. It is mainly designed to rearrange ideas about collaboration drawn from the literature in order to develop a conceptual framework for categorizing modes of collaboration based on how communication patterns shape four modes of collaboration. In the conclusion and discussion part, practical implications, limitations of this study, and further studies are discussed. In particular, the practical implications propose communication patterns suitable for five stages of collaboration processes. As the collaboration initiation or set-up stage is critical, extensive face-to-face communication is recommended in the auditing stage. In the execution stage, media-based communication can be actively utilized, because collaborators will mostly exchange explicit codified knowledge supported by IT. The evaluation and reinforcement stages concentrate on tacit knowledge exchange and explicit knowledge evaluation, which requires intensive face-to-face communication including negotiations for evaluating collaboration outcomes and partnership.