• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.129-132
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• 1996

In this paper, we suggest a framework to represent the fuzziness in knowledge base as a perspective of the object-oriented paradigm. We divide the knowledge base in two parts. One is the object-base that stores the fuzzy propositions and the explanatory databases. The other is the rule-base that manages the rules between the fuzzy propositions. As the first step, we have to develop a new fuzzy object model that gives an easy way to represent the fuzzy propositions, that is, the fuzzy knowledge in the real world.

• 한국경영정보학회:학술대회논문집
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• 한국경영정보학회 2008년도 춘계학술대회
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• pp.1-6
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• 2008

Organizations are increasingly adopting Knowledge Management Systems (KMS) to effectively manage knowledge within the organization and realize firm and operational level benefits. However, many KMS implementations fail to yield desired outcomes due to the lack of understanding of the antecedent of successful knowledge management. Prior studies have established that organizational cultural values are one of the key enablers of knowledge management. We develop a computational model of organizational knowledge processes and employ simulations to examine the impact of KMS in different organizational cultural settings. We find that cultural values that govern the employees' predisposition towards seeking knowledge from others have a greater influence on KMS effectiveness than those that govern the employees' attitudes towards sharing their knowledge with others. We also find that organizations with cultures that foster high levels knowledge sharing behaviors can expect performance gains if KMS implementations incorporate knowledge seeking activities into the employees' work processes.

• Journal of Information Technology Applications and Management
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• 제18권1호
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• pp.75-100
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• 2011

For decades, thousands of corporation introduced knowledge management systems to respond knowledge-based society. However, it seems that the systems merely focusing on knowledge accumulation and its sharing have been bounded by many restrictions in terms of new knowledge creation based on the life cycle of knowledge management systems. Moreover, recently, a variety of knowledge management activities regarding organization, systems, and process is emphasized as a strategic asset for a corporation to create core knowledge. Therefore, this study adopted the Csikszentmihalyi's flow theory to investigate the factors affecting knowledge creation and the success factors of knowledge management systems in virtual space. Prior studies argued that flow experience should be a prerequisite for creative knowledge creation. In that vein, this research revealed the causal relationships for flow experience between the determinants of clear goal, immediate feedback, congruence of challenge and skill. Additionally, it empirically examined how flow experience affected the exploratory behavior of knowledge creation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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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.

• 한국콘텐츠학회논문지
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• 제16권7호
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• pp.19-30
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• 2016

본 연구는 지식서비스기업의 경영성과 영향 요인을 규명하고자 AHP 분석 방법론을 활용하여 지식서비스 비즈니스 모델 구성요인 간의 상대적 중요도를 도출하고 기존 제조업을 대상으로 한 선행연구 결과와 비교분석하였다. 연구결과, 지식서비스기업 비즈니스모델의 상위요인들의 상대적 중요도는 제품/서비스(0.361), 마케팅(0.251), 재정능력(0.234), 인프라(0.154)순으로 나타났으며, 하위요인들의 상대적 중요도는 가치제안(0.254), 수익원(0.154), 핵심활동(0.107), 핵심자원(0.100), 채널(0.086) 순으로 나타났다. 또한, 제조업에서는 마케팅이 상대적 중요도가 높은데 반해 지식서비스업에서는 제품/서비스로 나타나 산업특성간의 상대적 중요도가 다르다는 것을 확인할 수 있었다. 본 연구는 산업특성별 비즈니스모델 구성요인의 중요도가 다름을 인식하고 산업별 특성을 고려하여 비즈니스모델을 수립하는데 유용한 시사점을 제공한다.

• 한국음향학회지
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• 제38권5호
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• pp.607-613
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• 2019

본 논문은 external knowledge를 사용한 lattice 없는 상호 정보 최대화(Lattice Free Maximum Mutual Information, LF-MMI) 기반 음향 모델링 방법을 제안한다. External knowledge란 음향 모델에서 사용하는 학습 데이터 이외의 문자열 데이터를 말한다. LF-MMI란 심층 신경망(Deep Neural Network, DNN) 학습의 최적화를 위한 목적 함수의 일종으로, 구별 학습에서 높은 성능을 보인다. LF-MMI에는 DNN의 사후 확률을 계산하기 위해 음소의 열을 사전 확률로 갖는다. 본 논문에서는 LF-MMI의 목적식의 사전 확률을 담당하는 음소 모델링에 external knowlege를 사용함으로써 과적합의 가능성을 낮추고, 음향 모델의 성능을 높이는 방법을 제안한다. External memory를 사용하여 사전 확률을 생성한 LF-MMI 모델을 사용했을 때 기존 LF-MMI와 비교하여 14 %의 상대적 성능 개선을 보였다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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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.

• 한국기술혁신학회:학술대회논문집
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• 한국기술혁신학회 2006년도 춘계학술대회
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• pp.3-17
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• 2006

Ideas do not become exhausted, and there are no diminishing returns in the creation of knowledge. Nonetheless, growth ultimately ceases in this simplest model of endogeneous innovation. But, if we treat knowledge capital as a public capital considering of its non-appropriable benefits, economic growth can be sustained in the economy. We showed that considering goodness of fit of regression model, we can see that the empirical evidence is strongly in favor of the character of knowledge as the public knowledge capital. So, we can expect that by product differentiation, economic growth can be sustained in the Korean economy.

• 지식경영연구
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• 제17권4호
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• pp.57-76
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• 2016

The objective of this study is to explore attendees' motivation, satisfaction, and intention to revisit the World Knowledge Forum (WKF). The importance of this study is that it is the first to examine the WKF, which is a renowned, prestigious global forum in Korea. In this study, the goal framing theory is adopted to hypothesize a theoretical model to explain and predict attendees' motivation, satisfaction, and intention to revisit the forum. The hypothesized model is validated empirically using a sample of 305 attendees of the WKF in 2015. Ultimately, of eight hypotheses, seven are verified and one is rejected. According to the results of an empirical analysis, our study validates the usefulness of the goal framing theory and suggests an examination of its theoretical and practical implications.

• Asia pacific journal of information systems
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• 제14권2호
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• pp.115-130
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• 2004

This paper proposes how to build an expert profile database in KMS, which provides the information of expertise that each expert possesses in the organization. To manage tacit knowledge in a knowledge management system, recent researches in this field 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 so that users can contact them for help. In this paper, we develop a framework to automate expert classification using a text categorization technique called Vector Space Model, through which an expert database composed of all the compiled profile information is built. This approach minimizes the maintenance cost of manual expert profiling while eliminating the possibility of incorrectness and obsolescence resulted from subjective manual processing. Also, we define the structure of expertise so that we can implement the expert classification framework to build an expert database in KMS. The developed prototype system, "Knowledge Portal for Researchers in Science and Technology," is introduced to show the applicability of the proposed framework.