• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권1호
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• pp.1-7
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• 2011

Most of expert systems use the text-oriented knowledge bases. However, knowledge management using the knowledge bases is considered as a huge burden to the knowledge workers because it includes some troublesome works. It includes chasing and/or checking activities on Consistency, Redundancy, Circulation, and Refinement of the knowledge. In those cases, we consider that they could reduce the burdens by using relational database management systems-based knowledge management infrastructure and convert the knowledge into one of easy forms human can understand. Furthermore they could concentrate on the knowledge itself with the support of the systems. To meet the expectations, in this study, we have tried to develop a general-purposed knowledge conversion tool for expert systems. Especially, this study is focused on the knowledge conversions among text-oriented knowledge base, relational database knowledge base, and decision tree.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 추계학술대회 논문집
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• pp.142-148
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• 1993

Recectly, development of expert system utilizing the domain specific knowledge focuses upon the machining operations. This paper describes an expert system for selecting the optimum grinding wheel based on the Analytic Hierarchy Process and Fuzzy Logic. Knowledge-base, in this system, for selecting of grinding wheel is designed to appling the knowhow and experience knowledge of skilled hands. In this paper, firstly determination method of fuzzy membership function utilizing the qualitative knowledge, and then selection of the optimum wheel from among the available components according to Saaty's priority rule are described. Lastly,some implementation results are suggested.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.447-450
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• 2003

In this research, we propose an automatic knowledge acquisition and composite knowledge expression mechanism based on machine learning and relational database. Most of traditional approaches to develop a knowledge base and inference engine of expert systems were based on IF-THEN rules, AND-OR graph, Semantic networks, and Frame separately. However, there are some limitations such as automatic knowledge acquisition, complicate knowledge expression, expansibility of knowledge base, speed of inference, and hierarchies among rules. To overcome these limitations, many of researchers tried to develop an automatic knowledge acquisition, composite knowledge expression, and fast inference method. As a result, the adaptability of the expert systems was improved rapidly. Nonetheless, they didn't suggest a hybrid and generalized solution to support the entire process of development of expert systems. Our proposed mechanism has five advantages empirically. First, it could extract the specific domain knowledge from incomplete database based on machine learning algorithm. Second, this mechanism could reduce the number of rules efficiently according to the rule extraction mechanism used in machine learning. Third, our proposed mechanism could expand the knowledge base unlimitedly by using relational database. Fourth, the backward inference engine developed in this study, could manipulate the knowledge base stored in relational database rapidly. Therefore, the speed of inference is faster than traditional text -oriented inference mechanism. Fifth, our composite knowledge expression mechanism could reflect the traditional knowledge expression method such as IF-THEN rules, AND-OR graph, and Relationship matrix simultaneously. To validate the inference ability of our system, a real data set was adopted from a clinical diagnosis classifying the dermatology disease.

• 산업경영시스템학회지
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• 제31권4호
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• pp.59-65
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• 2008

전문가시스템의 성공을 좌우하는 지식추출은 주요 애로공정 중의 하나로 알려져 있다 설상가상으로 전문가의 부재, 새로운 또는 복잡한 문제 등 영역의 특성상 전문가시스템 개발은 실패할 수 있다. 이러한 문제점을 극복하기 위하여 본 논문에서는 KACE 구조를 제안하였다 본 구조는 작업 발생기, 작업 실행기, 작업 평가기, 규칙 발생기와 전문가시스템 등 5개의 주요 요소로 구성되어 있다. 이 구조를 이용하여 NP-complete인 일정계획 문제에 대한 전문가시스템이 어떻게 구축될 수 있는가를 예시하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.568-571
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• 2004

In this study, we propose an efficient expert system (ES) construction mechanism by using dynamic knowledge map (DKM) and database management systems (DBMS). Generally, traditional ES and ES developing tools has some limitations such as, 1) a lot of time to extend the knowledge base (KB), 2) too difficult to change the inference path, 3) inflexible use of inference functions and operators. First, to overcome these limitations, we use DKM in extracting the complex relationships and causal rules from human expert and other knowledge resources. Then, elation database (RDB) and its management systems will help to transform the relationships from diagram to relational table. Therefore, our mechanism can help the ES or KBS (Knowledge-Based Systems) developers in several ways efficiently. In the experiment section, we used medical data to show the efficiency of our mechanism. Experimental results with various disease show that the mechanism is superior in terms of extension ability and flexible inference.

• 한국경영과학회지
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• 제30권1호
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• pp.129-147
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• 2005

In Knowledge Management Systems (KMS), tacit knowledge which is usually possessed as forms like know-how, experiences, and etc. is hard to be systemized while managing explicit knowledge is comparatively easy using information technology such as databases, Recent researches in knowledge management 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 propose an intelligent expert search framework to provide search capabilities for experts in similar or related fields according to the user's 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 test applicability and practicality of the proposed framework, the prototype system, Knowledge Portal for Researchers in Science and Technology, was developed.

• 지식경영연구
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• 제6권2호
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• pp.149-168
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• 2005

Owing to the limits of IT System-driven knowledge management(KM) for innovation processes, alternative KM methods has been suggested such as: (1) the knowledge network of experts or (2) communities-of-practice. This study analyzes two cases in terms of on-line expert knowledge networks for problem-solving, with the dimensions of analysis based on a theoretical framework. By analyzing the cases of S company's expert network and Naver's Ji-sik-iN, we found that system quality(e.g., ease of use, accessibility, and searching function), information/knowledge quality(e.g., usefulness, accuracy, and timeliness), knowledge-sharing culture, social capital and relevant reward systems are important for stimulating a Q&A-based problem-solving knowledge network. Implications of the findings and future research directions are discussed.

• 대한조선학회논문집
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• 제51권2호
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• pp.138-147
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• 2014

This paper proposed an application of expert system to submarine arrangement design. Since all components of the submarine should be placed in a restricted place called pressure hull, expert knowledge has great effects on design of submarine arrangement. In this regard, a suitable knowledge-based expert system shell was applied to design of submarine arrangement process. To use expert system on the design of submarine arrangement effectively, a template model for submarine arrangement, which is proper to use in optimum design process, was developed. The proposed system was applied to simplified example of submarine arrangement problem to choose optimal design alternative. From this study, it was verified that expert system could be used in design of submarine arrangement with effect.

• 지능정보연구
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• 제4권2호
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• pp.117-128
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• 1998

CBR is a knowledge-based system that utilizes the previous knowledge or experience to solve the current problem. In previous CBR research, the emphases are mainly put on the development of more sophisticated indexing mechanism for past cases or the most similar case retrieving methodology out of a group of previous cases. In this paper, discussed is a CBR system that is able to take advantage of the case or knowledge that does not belong to the past in the telecommunications internetworking design area. And the architecture for such CBR system is proposed. Finally, the performance of the CBR system is shown through an ablation experiment.

• 제어로봇시스템학회논문지
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• 제14권5호
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• pp.473-482
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• 2008

In this paper we propose an expert system for content-based image retrieval with object database. The proposed system finds keyword by using knowledge-base and feature of extracted object, and retrieves image by using keyword based image retrieval method. The system can decrease error of image retrieval and save running time. The system also checks whether similar objects exist or not. If not, user can store information of object in object database. Proposed system is flexible and extensible, enabling experts to incrementally add more knowledge and information. Experimental results show that the proposed system is more effective than existing content-based image retrieval method in running time and precision.