• 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.

• 정보관리연구
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• 제24권4호
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• pp.43-57
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• 1993

본 논문은 인공지능(artificial intelligence) 및 전문가 시스템(expert system)의 기본 개념과 이에 적용되고 있는 특정한 기술인 퍼지 이론(fuzzy logic)을 논하고 있으며, 지난 몇 년 동안 탐색 중개인으로서의 전문가 시스템을 조사해 보았다. 이러한 전문가 시스템은 1) 특정한 데이터베이스에 관련된 질문서 작성을 도와주며, 2) 탐색용어나 데이터베이스 선정에 관한 결정을 보조하고, 3) 탐색중에 있는 이용자에게 조언(助言)을 해주고 있다. 또한 전문가 시스템을 개발하는 에 있어 어려움 및 제한점(制限點)을 논의하고 있다.

• 지능정보연구
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• 제9권2호
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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.

• 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.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.73-79
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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.

• 대한전기학회논문지:전력기술부문A
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• 제53권10호
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• pp.565-572
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• 2004

This paper proposes an expert system which can enhance the accuracy of real-time bus reconfiguration strategy by adopting local minimum tree search method and minimize the spreading effect of the fault by considering totally the operating condition when a main transformer fault occurs in the automated substation. The local minimum tree search method to expand the best-first search method. This method has an advantage which can improve the performance of solution within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. And, second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules for the obtained switching candidate set. Also, this paper studies the generalized distribution substation modelling using graph theory and a substation database is designed based on the study result. The inference engine of the expert system and the substation database is implemented in MFC function of Visual C++. Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and local minimum tree search solution based on diversity event simulations for typical distribution substation.

• 한국콘텐츠학회논문지
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• 제16권12호
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• pp.458-467
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• 2016

사용자들에게 필요한 대표적인 연구 결과물과 조언을 제공할 수 있는 대용량 학술 정보를 이용하여 특정 관심 분야의 전문가를 검색하는 기법에 대한 연구가 요구되고 있다. 기존의 전문가 검색 기법은 사용자 프로필, 최근 활동 분석을 기반으로 전문가를 검색하기 때문에 사용자의 프로필 또는 활동 정보를 파악하지 못할 경우 전문가를 판별하기 어려운 문제점이 있다. 본 논문에서는 논문의 중요성 및 품질을 이용한 전문가 검색 기법을 제안한다. 논문의 중요성은 논문의 희소성과 최근 이슈가 되는 토픽을 고려하여 계산한다. 논문의 품질은 인용 수, 저널의 IF, 최신성, 저자관계를 고려하여 논문의 영향력을 평가한다. 제안하는 기법의 우수성을 보이기 위해 기존 기법과 정확률과 재현율 관점에서 성능평가를 수행한다.

• 한국정보통신학회논문지
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• 제16권1호
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• pp.183-190
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• 2012

본 연구는 연구논문 및 저자 프로파일을 기반으로 상호 협력이 가능한 전문가 검색 시스템을 구축한다. 제안한 방법론은 다음과 같다. 첫째, 입력 키워드와 가장 연관성 높은 키워드를 검색하기 위한 가중치 부여 기법을 제안하고, 둘째, 이 기법을 통해 전문가를 효율적으로 검색하는 방안을 제안한다. 우선적으로 논문에서 키워드와 저자 프로파일을 추출하고, 이를 통하여 전문가를 검색할 수 있도록 한다. 이것은 소셜 네트워크의 여러 분야에서 활용할 수 있다. 이러한 정보는 여러 시스템에 분산되어 있다. 이렇게 분산된 데이터를 통합하기 위한 기술로 멀티 온토롤지를 이용하는 기법을 제안한다. 멀티 온톨로지는 메타 온톨로지, 인스턴스 온톨로지, 로케이션 온톨로지와 연관관계 온톨로지로 구성되고, 연관관계 온톨로지는 동적으로 키워드 연관관계 분석을 통해 구축된다. 이 멀티 온톨로지를 이용하여 전문가 망을 제공하고, 이것은 키워드의 연관관계 추적을 통한 전문가 검색이 가능하도록 한다. 이를 통하여 전문가들의 연구물을 확인할 수 있도록 제공함으로써 세부 전문분야를 확인할 수 한다.

• 대한전기학회논문지
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• 제43권3호
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• pp.363-371
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• 1994

This thesis investigates an expert system(ES) to propose fault restoration plan by utilizing tree search strategies. In order to cope with an extensive amount of data and frequent breaker switching operations in distribution systems, the database of system configuration is constructed by using binary trees. This remarkably enhances the efficiency of search algorithm and makes the proposed ES easily adaptable to system changes due to switching operations. The rule-base is established to fully utilize the meris of tree-structured database. The inferring strategy is developed mainly based on the best-first search algorithm to increase computation efficiency. The proposed ES has been implemented to efficiently deal with large distribution systems by reducing computational burden remarkably compared with the conventional ES's.

• 한국해양공학회지
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• 제26권4호
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• pp.8-14
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• 2012

Two dimensional nesting is a common problem in industries such as the shipbuilding, automotive, clothing, shoe-making, and furniture industries, in which various parts are cut off from stock or packed in a flat space while minimizing waste or unoccupied space. Nesting is known as an NP-complete problem, which has a solution time proportional to the superpolynomial of the input size. It becomes practically impossible to find an optimal solution using algorithmic methods as the number of shapes to nest increases. Therefore, heuristic methods are commonly used to solve nesting problems. This paper presents an expert system that uses a heuristic search method based on an evaluation function for nesting problems, in which parts and stock are represented by pixels. The system is developed in CLIPS, an expert system shell, and is applied to four different kinds of example problems to verify its applicability in practical problems.