• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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• pp.111-120
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• 1999

Although the concept of viewing knowledge as a critical resource has been widely accepted in prior studies, it is not fully understood how to acquire available knowledge in order to improve organizational effectiveness. However, it si sure that organizational knowledge management should pursuit the achievement of the business goal by delivering relevant and useful information to the right person at the right time. Group Support System (GSS) can play an important role to transfer scatter information into meaningful business knowledge for supporting strategic corporate decision-making. This study proposes a fuzzy GSS framework for acquiring workgroup knowledge from individual memory and aggregating workgroup knowledge to organizational knowledge. This study also proposes an architecture to support the fuzzy GSS framework. The architecture consists of user agents, information management agents, and a fuzzy model manager. To illustrate how the fuzzy GSS framework can be used to support the whole process of organization knowledge acquisition, an Internet-based GSS was developed and applied in a marketing decision process. It showed that the framework was effective for acquiring organizational knowledge.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.564-568
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• 2005

Recently, Knowledge Management (KM) has been applied to construction industry. Surprising, there is few studies that address the most fundamental problem in KM: people may prefer not to share their knowledge so as to preserve their intellectual or unique values in the organization. Without the premise of each individual's willingness to share knowledge, there will be no valuable input for the IT system and, thus, no knowledge management at all. This paper aims to model the behavioral dynamics of knowledge sharing and to design an incentive system that may facilitate knowledge sharing for construction companies. In this paper, a game-theory based model will be developed, and the framework for designing an incentive system will be proposed according to the model.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2003년도 춘계학술대회
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• pp.474-483
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• 2003

A number of studies for corporate bond rating classification problems have demonstrated that artificial intelligence approaches such as Case-based reasoning (CBR) can be alternative methodologies to statistical techniques. CBR is a problem solving technique in that the case specific knowledge of past experience is utilized to find a most similar solution to the new problems. To build a successful CBR system to deal with human information processing, the representation of knowledge of each attribute is an important key factor We propose a hybrid approach of using fuzzy sets that describe the approximate phenomena of the real world because it handles inexact knowledge represented by common linguistic terms in a similar way as human reasoning compared to the other existing techniques. Integration of fuzzy sets with CBR is important to develop effective methods for dealing with vague and incomplete knowledge to statistical represent using membership value of fuzzy sets in CBR.

• 지능정보연구
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• 제1권2호
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• pp.57-71
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• 1995

This paper presents a rule extraction algorithm RE to acquire explicit rules from trained neural networks. The validity of extracted rules has been confirmed using 6 different data sets. Based on experimental results, we conclude that extracted rules from RE predict more accurately and robustly than neural networks themselves and rules obtained from an inductive learning algorithm do. Rule extraction algorithm for neural networks are important for incorporating knowledge obtained from trained networks into knowledge based systems. In lieu of this, the proposed RE algorithm contributes to the trend toward developing hybrid and versatile knowledge-based system including expert systems and knowledge-based decision su, pp.rt systems.

• 한국전자거래학회지
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• 제5권2호
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• pp.143-150
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• 2000

This paper presents a methodology how to utilize management of research scheduling plan, processing, and results using Web Knowledge Database System, which integrates research knowledge management model under the Research ＆ Development Environment. The content of this paper consists of description on utilization of the Web Knowledge Database System, sharing of the Research Knowledge through design data review, communications, and management of research knowledge flow during the Research ＆ Development Period.

• 동의생리병리학회지
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• 제23권4호
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• pp.745-750
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• 2009

The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.

• 한국도서관정보학회지
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• 제40권2호
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• pp.139-159
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• 2009

본 연구의 목적은 이용자 지향적인 정보검색을 수행하기 위한 질의확장용 지식베이스를 구축하는 것이다. 이를 위해 개념기반 정보검색방법과 통계적 기반 정보검색방법을 이용한 지식베이스 구축에 관련된 다양한 이론 연구를 수행하였다. 이들 지식베이스 구축방법에 있어서 공통된 가설은 연관용어의 출현은 문헌집합내의 동시출현 빈도임을 재확인하였고, 이 가설을 근거로 색인파일 알고리즘과 부울 논리의 And 연산자를 이용하여 질의확장용 지식베이스를 구축하였다. 본 지식베이스의 실험 주제는 교육학이며, 교육학개론이란 단행본을 이용하여 색인어들의 연관용어를 자동으로 제시해줄수 있는 실험용 지식베이스를 구축하였다. 실험용 지식베이스는 자연어색인방법과 통제어색인방법을 이용하여 두 개의 지식베이스를 구축해 각 지식베이스 시스템의 질의확장 성능에 대한 평가 작업을 수행하였다.

• 한국안전학회지
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• 제10권3호
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• pp.115-119
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• 1995

The effectiveness of an ensuring the facility safety depends on the ability to train the worker efficiently and strategy of facility control. This requires the instructor's awareness of the worker's current knowledge, in the specific areas of the worker's lacks of knowledge, and preferred methods of training. This paper presents a development of knowledge based on CBT system which will reduce the role of instructor from the training loop and be used the high technological method such as computer animation technique.

• 지능정보연구
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• 제9권3호
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• pp.49-63
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• 2003

본 논문은 효율적이고 신뢰성 있는 전문가시스템을 구축하기 위한 도구를 제안하고 구현한다. 전문가 시스템에서 추론은 특정 전문분야의 지식베이스에 저장된 지식을 기반으로 행해진다. 이 때 전문가 시스템이 신뢰할 수 있는 추론의 결과를 얻기 위해서는 다양한 형태의 지식들이 이용되고, 지식의 정확성 및 일관성이 유지되어야 한다. 이러한 관점에서 본 논문은 지식이 지식베이스에 첨가되기 전에 지식의 오류를 점검함으로써 오류가 없는 지식들을 선택적으로 지식베이스에 첨가하여, 지식의 정확성 및 일관성을 유지하는 지식관리 시스템을 구축했다. 아울러 본 논문은 전문가 시스템이 추론과정에서 다양한 지식을 이용하도록 절차적 지식과 데이터베이스에 저장된 선언적 지식을 호출하여 사용할 수 있도록 했다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 춘계학술대회 논문집
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• pp.801-802
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• 2007