• Knowledge Management Research
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• v.4 no.2
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• pp.19-34
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• 2003

This paper analyzes 96 Korean companies to illustrate the relationship between the knowledge management strategies and task characteristics. Knowledge management strategies can be categorized as being codification- and personalization-oriented. Task characteristics are analyzed from the perspective of content-oriented, process-oriented, number of exceptions, and analyzability. These results illustrate how companies should align the knowledge management strategies with task characteristics. It is found that codification strategy is more likely to be associated with high content-oriented and high analyzability task, and personalization strategy is with high process-oriented task. The survey result confirms that managers should adjust knowledge management strategies in view of the characteristics of the task.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.674-679
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• 1987

Process failures can occur at any time during operation, so a continuous effort of fault detection, diagsis, and correction is required. Expert system paridigm has been regarded as a promising approach to real time process supervisory control especially to fault diagnosis. The most important aspects of fault diagnostic expert systems(FDES) are the problem-solving inference strategy and knowledge organizations. The necessity of FDES, the nature of diagnostic knowledge, the representation of knowledge, and the inference mechanism of FDES, et al. are described, which are announced by previous researchers. And the existing FDES are categorized and critically reviewed in this work.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1705-1711
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• 1991

On-line fault detection and diagnosis has an increasing interest in a chemical process industry, especially for a process control and automation. The chemical process needs an intelligent operation-aided workstation which can do such tasks as process monitoring, fault detection, fault diagnosis and action guidance in semiautomatic mode. These tasks can increase the performance of a process operation and give merits in economics, safety and reliability. Aiming these tasks, series of researches have been done in our lab. Main results from these researches are building appropriate knowledge representation models and a diagnosis mechanism for fault detection and diagnosis in a chemical process. The knowledge representation schemes developed in our previous research, the symptom tree model and the fault-consequence digraph, showed the effectiveness and the usefulness in a real-time application, of the process diagnosis, especially in large and complex plants. However in our previous approach, the diagnosis speed is its demerit in spite of its merits of high resolution, mainly due to using two knowledge models complementarily. In our current study, new knowledge representation scheme is developed which integrates the previous two knowledge models, the symptom tree and the fault-consequence digraph, into one. This new model is constructed using a material balance, energy balance, momentum balance and equipment constraints. Controller related constraints are included in this new model, which possesses merits of the two previous models. This new integrated model will be tested and verified by the real-time application in a BTX process or a crude unit process. The reliability and flexibility will be greatly enhanced compared to the previous model in spite of the low diagnosis speed. Nexpert Object for the expert system shell and SUN4 workstation for the hardware platform are used. TCP/IP for a communication protocol and interfacing to a dynamic simulator, SPEEDUP, for a dynamic data generation are being studied.

• Knowledge Management Research
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• v.19 no.2
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• pp.163-185
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• 2018

In order to solve problems in an uncertain and complicated management environment of the modern world, a creative solution that combines diverse perspectives, knowledge, and effort based on diversity within an organization is required. Smart work environment provides an opportunity to express the potential diversity of an individual, extending the source of ideas to the organization, enhancing communication, and linking and sharing information and knowledge. So, this results in increased creative behavior. The purpose of this study is to investigate the effect of the process of connecting and sharing information and knowledge of organizational members on creative behavior and the effect of smart work environment in the process. The purpose of this study is to identify roles of job autonomy, self-efficacy, knowledge sharing and smart work environment in creative process. For the study, 353 surveys with work use group(156 people) and unused group(197 people). Statistical analysis included validity and reliability analysis, structural model analysis. The results showed that self-efficacy and job autonomy had positive effects on creative behavior and knowledge sharing, and job autonomy had a positive effect on self-efficacy. Knowledge sharing has a positive effect on creative behavior, and mediates the relationship between self-efficacy, job autonomy and creative behavior. Particularly, knowledge sharing has a more positive effect on smart work use group. In case of smart work use group, self-efficacy and job autonomy have a relatively high influence on knowledge sharing rather than direct influence on creative behavior appear. This result implies that the achievements of smart work are revealed in terms of knowledge sharing and creative behavior.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.99-106
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• 1998

In this paper, we have constructed an expert system for semiconductor chip encapsulation which combines a knowledge-based system with CAE software. The knowledge-base module includes heuristic and pre analysis knowledge for evaluation and redesign. Evaluation of the initial design and generation of redesign recommendations can be developed from the rules as applied to a given chip package. The CAE programs can be used for simulating the filling and packing stage of encapsulation process. The expert system is a new tool which enables package design or process conditions with high yields and high productivity.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.4
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• pp.87-97
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• 2012

A knowledge map is a diagramed network among knowledge which is related with each other in terms of the referential navigation. To formally as well as structurely represent various contextual use of knowledge, the ontology technology has been recommended to be applied. This research proposes a methodology to build the ontology-based knowledge map promoting referential navigation between knowledge. To prove the validity of the proposed concepts, an ontology-based knowledge map is designed as an example, which demonstrates whether the designed knowledge network in the knowledge map is underpinned by the referential navigation between knowledge.

• The Journal of Information Systems
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• v.18 no.3
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• pp.135-154
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• 2009

As the knowledge is recognized as a core factor of organization's competitiveness and creation of value added, the importance of knowledge management is also increased. To achieve the successful knowledge management, it is important to establish strategy that consider essential purpose of knowledge management such as creating and sharing of knowledge resource, improving performance, and continuing organizational innovation within the organization and influence factor inside and outside of organization. Until now, however, the research for knowledge management strategy was mostly limited to the statistical analysis based on the unilinear causality model, and systematic access and analysis that consider interaction and feedback structure between factors. In this paper, we developed the novel decision-making framework for successful strategy establishment by applying the analytic network process(ANP). Specifically. we derive clusters and components to decide the interaction and feedback structure between the elements of knowledge management by literature studies. And we produced relative importance and preference of clusters, components and alternatives dealing with feedback structure through the survey of experts in the field or related one of knowledge management. In result of this study, we expect that it will help the knowledge officer to decide establishing knowledge management strategy.

• Knowledge Management Research
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• v.2 no.1
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• pp.45-63
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• 2001

The role of knowledge as the key source of potential advantage for organizations and economies has become a hotly debated topic. Some studies found that organizations had their own knowledge management styles. Knowledge Management draws form existing resources that organizations may already have in place. Checking the organization's infrastructures for Knowledge Management is the first step for Knowledge Management. Although the as- is analysis of organizations before knowledge management is important, but there is no study on the readiness for Knowledge Management. This study reports on the development of an instrument designed to measure the readiness of an organization for knowledge Management. Starting with the literature, 4 dimensions - strategy, process, culture/people, and technology - and 18 factors were identified. Then, a questionnaire for measuring readiness was created. Finally, the instrument was pilot tested to prove its reliability and validity. Following the pilot test, the factors all demonstrated acceptable levels of reliability. The result is 19 factors instrument comprising 4 dimensions which provide a useful tool for measuring the readiness for Knowledge Management.

• Asia pacific journal of information systems
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• v.8 no.1
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• pp.43-64
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• 1998

Cooperative query answering is a research effort to develop a fault-tolerant and intelligent database system using the semantic knowledge base constructed from the underlying database. Such knowledge base has two aspects of usage. One is supporting the cooperative query answering process for providing both an exact answer and neighborhood information relevant to a query. The other is supporting ongoing maintenance of the knowledge base for accommodating the changes in the knowledge content and database usage purpose. Existing studies have mostly focused on the cooperative query answering process but paid little attention to the dynamic knowledge base maintenance. This paper proposes a multi-level knowledge representation framework called Knowledge Abstraction Hierarchy(KAH) that can not only support cooperative query answering but also permit dynamic knowledge maintenance, On the basis of the KAH, a knowledge abstraction database is constructed on the relational data model and accommodates diverse knowledge maintenance needs and flexibly facilitates cooperative query answering. In terms of the knowledge maintenance, database operations are discussed for the cases where either the internal contents for a given KAH change or the structures of the KAH itself change. In terms of cooperative query answering, four types of vague queries are discussed, including approximate selection, approximate join, conceptual selection, and conceptual join. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database application systems.