• IE interfaces
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• v.3 no.1
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• pp.31-38
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• 1990

This paper deals with two topics which are vital in fuzzy expert systems; one is how to build fuzzy knowledge base by fuzzy expertise modeling for representing knowledge with imprecise characteristic and the other is how to draw an inference from fuzzy knowledge base using translating rules. The result of this study provides the basic principle for constructing the fuzzy knowledge base and the fuzzy inference system.

• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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• pp.189-207
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• 1997

Recently, we have witnessed a host of emerging tools in the management support systems (MSS) area including the data warehouse/multidimensinal databases (MDDB), data mining, on-line analytical processing (OLAP), intelligent agents, World Wide Web(WWW) technologies, the Internet, and corporate intranets. These tools are reshaping MSS developments in organizations. This article reviews a set of emerging data management technologies in the knowledge discovery in databases(KDD) process and analyzes their implications for decision support. Furthermore, today's MSS are equipped with a plethora of AI techniques (artifical neural networks, and genetic algorithms, etc) fuzzy sets, modeling by example , geographical information system(GIS), logic modeling, and visual interactive modeling (VIM) , All these developments suggest that we are shifting the corporate decision making paradigm form information-driven decision making in the1980s to knowledge-driven decision making in the 1990s.

• Journal of the Korea Society for Simulation
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• v.10 no.4
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• pp.51-64
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• 2001

It is quite necessary that an organization's information network should be equipped with a proper security system based on its scale and importance. One of the effective methods is to use the simulation model for deciding which security policy and mechanism is appropriate for the complex network. Our goal is to build a foundation of knowledge-based modeling and simulation environment for the network security. With this environment, users can construct the abstracted model of security mechanisms, apply various security policies, and quantitatively analyze their security performance against possible attacks. In this study, we considered security domain from several points of view and implemented the models based on a systematic modeling approach. We enabled the model to include knowledge in modular fashion and provided well-defined guidelines for transforming security policy to concrete rule set.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.81-89
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• 1992

After much research on qualitative reasoning, the problem of ambiguities still hampers the practicality of this important AI tool. In this paper, the sources of ambiguities are examined in depth with a systems engineering point of view and possible directions to disambiguation are suggested. This includes some modeling strategies and an architecture of temporal inference for building unambiguous qualitative models of practical complexity. It is argued that knowledge of multiple levels in abstraction hierarchy must be reflected in the modeling to resolve ambiguities by introducing the designer's decisions. The inference engine must be able to integrate two different types of temporal knowledge representation to determine the partial ordering of future events. As an independent quantity management system that supports the suggested modeling approach, LIQUIDS(Linear Quantity-Information Deriving System) is described. The inference scheme can be conjoined with ordinary rule-based reasoning systems and hence generalized into many different domains.

• Knowledge Management Research
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• v.14 no.3
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• pp.1-13
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• 2013

This study investigates how relational activities within MNC network affect knowledge transfer and performance of subsidiary. We separated the possible relationships between headquarter and overseas subsidiaries by support level, interaction level, and conflict level, and compared the impact on knowledge transfer, and performance. To understand the knowledge sharing, development and performance, we use structural equation modeling to analyze data from subsidiaries in China.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.381-387
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• 1994

In this paper, we found the improved SPICE heat transfer modeling of impulsed magnetizing fixture system and investigated temperature characteristics using the proposed model. As the detailed thermal characteristics of magnetizing fixture can be obtained, the efficient design of the impulsed magnetizing fixture which produce desired magnet will be possible using our heat transfer modeling. The knowledge of the temperature of the magnetizing fixture is very important of forecast the characteristics of the magnetizing fixture which produce desired magnet will be possible using our heat transfer modeling. The knowledge of the temperature of the magnetizing fixture is very important to forecast the characteristics of the magnetizing circuits under different conditions. The capacitor voltage was not raised above 810[V] to protect the magnetizing fixture from excessive heating. The purpose of this work is to compute the temperature increasing for different magnetizing conditions. The method uses multi-lumped model with equivalent thermal resistance and thermal capacitance. The reliable results are obtained by using iron core fixture (stator magnet of air cleaner DC motor) coupled to a low-voltage magnetizer(charging voltage : 1000[V], capacitor : 3825[$\mu$F]. The modeling and experimental results are in close aggrement.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.237-243
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• 1993

This paper describes the design and implementation of a prototype modeling environment, Hypertext-based Integrated Modeling Environment(HIME). It implements a modeling framework, call Integrated Modeling Framework(IMF), which has been developed to increase model-related productivity and to integrate modeling knowledge and various information resources.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.502-509
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• 2013

Even if the need for English education in Korea is on the rise, too various perspectives on English education and the government's lack of consistency in the English education policy are said to be a negative factor in improving the English communication skills. The purpose of this study, in line with the knowledge and information society, is to develop ontology modeling for knowledge map of English education methodology and to make a contribution to English education policy of the country.

• IE interfaces
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• v.14 no.2
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• pp.164-171
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• 2001

We suggest a Business Performance Information System with Knowledge Discovery in Databases(KDD) as a key component of integrated information and knowledge management system. The proposed system measures business performance by considering both VA(Value-Added), which represents stakeholder's point of view and EVA(Economic Value-Added), which represents shareholder's point of view. In modeling of Business Performance Information System, we apply the following KDD processes : Data Warehouse for consistent management of a performance data, On-Line Analytic Processing(OLAP) for multidimensional analysis, Genetic Algorithms for exploring and finding dominant managing factors and Analytic Hierarchy Process(AHP) for applying expert's knowledge and experience. To demonstrate the performance of the system, we conducted a case study using financial data of Korean automobile industry over 16 years from 1981 to 1996, which is taken from database of KISFAS(Korea Investors Services Financial Analysis System).

• Knowledge Management Research
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• v.16 no.4
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• pp.69-87
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• 2015

Given the huge number of data produced by its users, SNS is a great source of customer insights. Since viral trends in SNS reflect customers' direct feedback, companies can draw out highly meaningful business insights when such data is effectively analyzed and managed. However, while the importance of understanding SNS big data keeps growing, the methods for analyzing atypical data such as SNS postings for business insights over product has not been well studied. This study aims to demonstrate the way to exploit topic modeling method to support marketing strategy generation and therefore leverage business process. First, we conducted topic modeling analysis for twitter data of Apple and Samsung smartphones. Then we comparatively examined the analysis results to draw meaningful market insights about each smartphone product. Finally, we draw out a strategic marketing recommendation for each smartphone brand based on the findings.