• Journal of Information Science Theory and Practice
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• v.7 no.2
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• pp.54-64
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• 2019

A theory of public knowledge is offered for the purposes of defining more clearly its role in information systems and classification schemas. Public knowledge is knowledge intended to be available for use in a public system. It is knowledge accessible to the public or knowledge in the public arena as opposed to the other seemingly multitudinous ways to describe knowledge. Furthermore, there are many different public arenas or small worlds. Public knowledge, irrespective of these different arenas, has four important overlying characteristics: It is consensual, it does not imply complete truth or certainty, it is autonomous, and it has a constant renewal of old knowledge with new knowledge. Each of these attributes has been culled from a study of the works of Patrick Wilson, Karl Popper, and John Ziman.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.81-95
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• 2000

A knowledge-based system with fuzzy production rules is a representation of static knowledge of an expert. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a strategy to reflect the dynamic nature of real system when we make inferences with a knowledge-based system. This paper proposes a strategy of dynamic inferencing for a knowledge-based system with fuzzy production rules. The strategy suggested in this paper applies weights of attributes of conditions of a rule in the knowledge-base. A degree of match(DM) between actual input information and a condition of a rule is represented by a value [0,1]. Weights of relative importance of attributes in a rule are obtained by AHP(Analytic Hierarcy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with MIN operator, into a single DM for the rule. In this way, overall DM for a rule changes depending on the importance of attributes of the rule. As a result, the dynamic nature of a real system can be incorporated in an inference with fuzzy production rules.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.50-54
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• 2001

Information systems development entails planning, analysis, design and construction phases. The analysis phase identifying user requirements is the most important of these phases. Since unidentified defects in the early phase causes increased work and costs as development proceeds, the quality of analysis results affects the quality of the resultant system. Major tasks in the analysis phase are data modeling and process modeling. Research on building a knowledge-based system for data modeling have been conducted much, however, not sufficiently for process modeling. As a system environment with high user interaction increases, research on process modeling methods and knowledge- based systems considering such environment are required. In this research, a process modeling framework for information systems with high user interaction is suggested and a knowledge-based system for supporting the suggested framework is implemented. A proposed model consists of the following tasks: event analysis, process analysis, and event/process interaction analysis. Event analysis identifies business events and their responses. Process analysis break down the processes of an enterprise into progressively increasing details. Decomposition begins at the function level and ends when the elementary process level is reached. Event/process interaction analysis verifies the results of process analysis and event analysis. A knowledge-based system for supporting a proposed process modeling framework is implemented in a web-based environment.

• Hwankyungkyoyuk
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• v.10 no.2
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• pp.51-62
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• 1997

The objective of this study was to review the meaning and problems of Scientific Knowledge and Ethical Value in Environmental Education. The ultimate goal of environmental education is shaping proenvironmental human behavior. The factors of human behavioral decision making are ideology, value, attitude and behavioral intentions. Ideology is a kind of belief system used by social groups to interpret their social world. The main elements of belief system are knowledge and value. The traditional thinking in education has been that we can change behavior by making human beings more knowledgeable and more valuable. In environmental education, the aim of scientific inquiry is to analysis cause-effect relation of human beings behavior and environmental phenomenon, and ethical education is to change the mind of human beings from zero-sum to positive-sum about the relations between human beings and natural environments. But, there are many problems of knowledge education and value education in environmental education. For example scientific knowledge without ethical value is dangerous to environment protection, and ethical value without scientific knowledge is vague. Therefore, we must recognize that the relationship of ethical value and scientific knowledge is not substitutional but complementary. The teaching-learning methods which can integrate knowledge and value in environmental education are rational decision making model. For this model, we can construct teaching contents with inquiry materials. To earn the benefits of specialization among several subjects in environmental education, social studies can focus on social science knowledge and decision making, science education can focus on pure natural science knowledge and scientific investigation, moral education can focus on problems of ethical value system, home economics can focus on practical action and environmental education(Environments in middle school, Ecology and Environments in high school) can integrate social-national science knowledge and ethical value in broad perspective about human beings and ecosystem. That is the method to protect from law of diminishing marginal utility of learning in environmental education.

• Journal of the Korean earth science society
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• v.32 no.5
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• pp.474-484
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• 2011

This study presents how a professional development program (PD) of K-12 teachers affects participants' use of the earth system approach and their perceptions of using the urban environment for their science teaching and lesson unit development. This study utilized mixed methods to collect and analyze the data. Eleven urban teachers' pre-post lessons (45 lessons) were analyzed quantitatively using a lesson plan analysis tool, modified by the author, and their lesson reflections were analyzed qualitatively. The findings of this study show that the PD program influences the teachers to choose more topics and content knowledge based on the earth system approach and to assess the topics and content knowledge with more appropriate methods. Specifically, the teachers use more urban environmental factors/topics in their post lesson to teach the environmental topics of urban area. However, according to the statistical analysis of pre-and postlesson plan scores, the accuracy of the earth system knowledge that participants used in their lessons did not change significantly (p<0.05) (Table 4), which means that the PD program did not affect the improvement of the teacher's content knowledge in earth system science. Implications of this study are discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.2
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• pp.214-221
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• 2015

A new classification system with 9 main categories and 56 subcategories for the Open Korean Knowledge Dictionary is proposed. The classification system setup is to prepare for the standard classification system to be used to manage effectively vast of terminologies which were published in the Open Korean Knowledge Dictionary and is meant to enhance the fifteen-year old classification system for the standard korean great dictionary to match up to the trend of the modern terminology. The new terminology classification system covering all the academic areas such as humanity, sociology, politics, science, medicine, agriculture, engineering, etc, is designed and proposed after investigating several classification systems. The classification system setup procedures follow as ${\circ}$ The classification system is designed and planed by both the classification system and the academic expert. ${\circ}$ Classification system design covers all the academic areas following National Science and Technology standard classification system after investigating several classification systems such as the National Research Foundation, National Science and Technology Standard Act, Ministry of Knowledge Economy. ${\circ}$ Poll and survey is made to collect comments from total 93 members of several academic areas. ${\circ}$ The poll result is reviewed among working group members and utilized to update the new terminology classification system. Reclassifications are made for the around 200,000 terms in electricity, computer, medicine, pharmacy, biology, and economics according to the new terminology classification system.

• Korean Journal of Cognitive Science
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• v.11 no.1
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• pp.67-80
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• 2000

Distributed cooperative information system is the one that has various knowledge sources as well as problem solving capabilities to get information in a distributed and heterogeneous data environment. In a distributed cooperative information system. a control mechanism to facilitate the available information is very important. and usually the role of the control mechanism determines the behavior of the total system In this research. we proposed a model of the distributed cooperative information system which is based on the multi-agent paradigm. We also implemented a test system to show l its feasibility. The proposed system makes the knowledge sources into agents and a special agent called 'facilitator' controls the cooperation between the knowledge agents The facilitator uses the knowledge granularity level to determine the sequence of the activation of the agents. In other words. the knowledge source with simple but fast processing mechanism activates first while more sophisticated but slow knowledge sources are activated late. In an environment in which we have several knowledge sources for the same topic. the proposed system will simulate the focusing mechanism of human cognitive process.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1165-1168
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• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.87-100
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• 2003

In managing organizational tacit knowledge, recent researches have shown that it is more applicable in many ways to provide expert search mechanisms in KMS to pinpoint experts in the organizations with searched expertise. In this paper, we propose an intelligent expert search framework to provide search capabilities for experts in similar or related fields according to the user′s information needs. In enabling intelligent expert searches, Fuzzy Abstraction Hierarchy (FAH) framework has been adopted, through which finding experts with similar or related expertise is possible according to the subject field hierarchy defined in the system. To improve FAH, a text categorization approach called Vector Space Model is utilized. To test applicability and practicality of the proposed framework, the prototype system, "Knowledge Portal for Researchers in Science and Technology" sponsored by the Ministry of Science and Technology (MOST) of Korea, was developed.

• International Journal of Contents
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• v.6 no.3
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• pp.1-4
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• 2010

The national management and retrieval service of the national scholar Content DB are very important. High quality content can improve the user's utilization and satisfaction and be a strong base for both the citation index creation and the calculation of journal impact factors. Therefore, the system is necessary to check data quality effectively. We have closely studied and developed a webbased data quality checking system that will support anything from raw digital data to its automatic validation as well as hands-on validation, all of which will be discussed in this paper.