• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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• pp.121-130
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• 1999

The objective of this paper is to apply Extended AND-OR Graph (EAOG)-related techniques to extract knowledge from a specific problem-domain and perform analysis in complicated decision making area. Expert systems use expertise about a specific domain as their primary source of solving problems belonging to that domain. However, such expertise is complicated as well as uncertain, because most knowledge is expressed in causal relationships between concepts or variables. Therefore, if expert systems can be used effectively to provide more intelligent support for decision making in complicated specific problems, it should be equipped with real-time inference mechanism. We develop two kinds of EAOG-driven inference mechanisms(1) EAOG-based forward chaining and (2) EAOG-based backward chaining. and The EAOG method processes the following three characteristics. 1. Real-time inference : The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matrix computation. 2. Matrix operation : All the subjective knowledge is delineated in a matrix form, so that inference process can proceed based on the matrix operation which is computationally efficient. 3. Bi-directional inference : Traditional inference method of expert systems is based on either forward chaining or backward chaining which is mutually exclusive in terms of logical process and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.511-515
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• 2001

Many intelligent agent systems are known to incorporate BDI architecture for cognitive reasoning. Since this architecture contains all the knowledge of world model and reasoning rule, it is very complex and difficult to handle. This paper describes a methodology to design and implement BDI architecture, BDIAXml based on XML for multi-agent systems. This XML-based BDI architecture is smaller than any other BDI architecture because it separates knowledge for reasoning from domain knowledge and enables knowledge sharing using XML technology. Knowledge for BDI mental state and reasoning is composed of specific XML files and these XML files are stored into a specific knowledge server. Most systems using BDIAxml architecture can access knowledge from this server. We apply this BDIAXml system to domain of Hospital Information System and show that this architecture performs more efficiently than other BDI architecture system in terms of knowledge sharing, system size, and ease of use.

• 인터넷정보학회논문지
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• 제7권4호
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• pp.67-77
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• 2006

기존의 도메인 지식 기반의 랩퍼 학습 방법은 도메인에 대한 정보를 바탕으로 해당 정보 소스에 대한 랩퍼를 생성한다. 용용 분야에 맞게 정의된 도메인 지식을 이용함으로써 정보 소스에서 제공하는 다양한 텍스트의 의미와 형태를 이해할 수 있다. 그러나 정보 소스에서 제공되는 모든 텍스트에 의미 인식의 근거가 되는 레이블이 붙어서 제공되는 것이 아니기 때문에 도메인 지식만을 이용해서 랩퍼를 학습하는 방법은 한계에 부딪힐 수밖에 없다. 이러한 문제를 해결하기 위해서 본 논문은 인터넷에 존재하는 다양한 웹 정보 소스에서 효율적이고 정확하게 랩퍼를 생성하는 도메인 지식 기반의 확률적 랩퍼 생성 시스템을 제안한다. 효율적이고 정확한 랩퍼 생성 시스템을 구축하기 위해서 도메인 지식뿐 아니라 상세 정보로 연결되어 있는 하이퍼링크와 엔티티 인식을 위한 확률 모델을 이용한다. 이와 같은 방법을 적용함으로써 사용자의 개입 없이 다양한 정보 소스에 대해서 보다 추출 성능이 좋은 랩퍼를 생성할 수 있다.

• 한국정밀공학회지
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• 제24권11호
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• pp.126-133
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• 2007

Tuberculosis (TB) is a chronic or acute infectious disease which damages more people than any other infectious diseases according to WHO estimates. In this paper, a new automatic detection system of tuberculosis bacilli by using their color information is proposed. Through the deep investigation of color and intensity compositions of tuberculosis images, new pre-processing and segmentation algorithms are suggested. Specific features of bacilli are extracted from the processed images and number counting is done by using domain-specific knowledge rules.

• 한국과학교육학회지
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• 제16권2호
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• pp.134-145
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• 1996

The purpose of this study was to investigate effects of mental capacity and mental demand on problem solving. Two kinds of tests were used for this study. One was FIT 752 test which required general knowledge, the other was Ohm's law test which required domain specific knowledge. The items of each test had the same logical structure and content knowledge but had different sizes of mental demand. The results of the study were summarized as follows: As mental demand of the items increased, the success rates decreased. The analysis of the hierarchical relation among items was that items with large mental demand were higher than those with small demand or at least the same level. According to the results, mental of an item was a significant factor affecting solving the problem. Effect of mental capacity on problem solving was different according to the kind of required knowledge to solve. Mental capacity was a significant factor affecting solving the FIT 752 task which required general knowledge. On the contary, solving the task which required domain specific knowledge, the results were different depending on subjects' chunk size. The results of problem solving of the groups which had small chunk size were that mental capacity was appeared a significant factor. However, results of problem solving of groups which had large chunk size were that mental capacity was not.

• 한국경영과학회지
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• 제19권1호
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• pp.17-40
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• 1994

The objectives of this paper are to apply fuzzy cognitive map (FCM)- related techniques to (1) extract causal knowledge from a specific problem-domain and (2) perform a series of causal analysis in complicated decision making area. We propose a set operation-based augmentation (SOBA) algorithm to combine multiple FCMs developed by multiple experts. Based on the SOBA knowledge acquisition algorithm, we can obtain a causal knowledge base fairly representing multiple experts' knowledge about a problem domain. The causal knowledge base built by SOBA algorithm can be described as a matrix form, guaranteeing mathematically compact operation compared with a production (if-then) knowledge base. We applied out method to stock market analysis problem whichis a typical of highly unstructured problems in OR/MS fields.

• 한국응용과학기술학회지
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• 제39권6호
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• pp.738-747
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• 2022

이 연구는 생태형 해양스포츠의 체육교육 적용을 위한 지식구조를 구성하는 것에 목적이 있다. 구체적인 종목으로는 배구형 게임인 비치발리볼과 바다수영이 설정되었으며 연구수행을 위하여 지식구조 분석틀을 활용하였다. 연구의 타당성을 확보하기 위하여 전문가협의를 실시하였다. 연구결과는 다음과 같다. 첫째, 2022개정 체육과 교육과정 시안에 기반한 지식구조를 마련하였다. 둘째, 생태형 해양스포츠의 체육수업 적용 기반을 마련하였다.셋째, 비치발리볼의 지식·이해 영역, 과정·기능 영역, 가치·태도 영역의 학습 내용을 제안하였다. 넷째, 바다수영의 지식·이해 영역, 과정·기능 영역, 가치·태도 영역의 학습 내용을 제안하였다. 이 연구는 향후 도입될 2022개정 체육과 교육과정의 실현된 모습을 미리 대비하였다는 것에 의미가 있다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2004년도 추계학술발표논문집(상)
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• pp.591-594
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• 2004

Existing methodologies and practical ontology development experiences have explored a broad spectrum of knowledge management challenges. Each has its own characteristics and evaluates only a subset of specific domain. However, there is still no one 'correct' way or methodology for developing ontologies. In this paper, we described a methodology for domain driven ontology development, covering the whole lifecycle from the formalization of domain to the evolution of ontologies.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.75-88
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• 2023

In a specific domain, experts have different understanding of domain knowledge or different purpose of constructing ontology. These will lead to multiple different ontologies in the domain. This phenomenon is called the ontology heterogeneity. For research fields that require cross-ontology operations such as knowledge fusion and knowledge reasoning, the ontology heterogeneity has caused certain difficulties for research. In this paper, we propose a novel ontology matching model that combines word embedding and a concatenated continuous bag-of-words model. Our goal is to improve word vectors and distinguish the semantic similarity and descriptive associations. Moreover, we make the most of textual and structural information from the ontology and external resources. We represent the ontology as a graph and use the SimRank algorithm to calculate the structural similarity. Our approach employs a similarity queue to achieve one-to-many matching results which provide a wider range of insights for subsequent mining and analysis. This enhances and refines the methodology used in ontology matching.

• 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.