• 제목/요약/키워드: Evaluation Case-Based Reasoning

검색결과 41건 처리시간 0.028초

보안위험분석을 위한 평가기반 CBR모델 (The Evaluation-based CBR Model for Security Risk Analysis)

  • 방영환;이강수
    • 한국정보과학회논문지:시스템및이론
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    • 제34권7호
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    • pp.282-287
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    • 2007
  • 정보시스템을 이용하는 금융, 무역, 의료, 에너지, 교육 등 사회 각 분야에서 정보화가 급속하게 진전되고 있다. 정보시스템에 대한 보안관리는 위험분석평가가 선행 되어야하며, 보안위험분석은 요구되는 정보보호서비스의 취약점을 해결하고 위협으로부터 시스템을 안전하게 관리할 수 있는 최선의 방법이다. 본 논문에서는 최적의 평가계획을 수립한 수 있는 평가사례기반추론 기능을 모델링하였다. 평가 사례기반추론(case-based reasoning) 기능은 보안위험분석평가를 프로젝트단위로 관리하며, 기존의 평가사례 간유사도를 평가하고, 유사한 평가 사례를 바탕으로 최적의 보안위험분석평가 계획을 수립할 수 있다.

DSS와 사례기반 추론의 결합 (Integrating Case-Based Reasoning with DSS)

  • 김진백
    • 경영과정보연구
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    • 제2권
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    • pp.169-193
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    • 1998
  • Case- based reasoning(CBR) offers a new approach for developing knowledge based systems. Unlike the rule-based paradigm, in which domain knowledge is encoded in the form of production rules, in the case-based approach the problem solving experience of the domain expert is encoded in the form of cases stored in a casebase(CB). CBR allows a reasoner (1) to propose solutions in domains that are not completely understood by the reasoner, (2) to evaluate solutions when no algorithmic method is available for evaluation, and (3) to interprete open-ended and ill-defined concepts. CBR also helps reasoner (4) take actions to avoid repeating past mistakes, and (5) focus its reasoning on important parts of a problem. Owing to the above advantages, CBR has successfully been applied to many kinds of problems such as design, planning, diagnosis and instruction. In this paper, I propose case-based DSS(CBDSS). CBDSS is an intelligent DSS using CBR technique. CBDSS consists of interface, case-based reasoner, maintainer, casebase management system, domain dependent CB, domain independent CB, and so on.

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Fuzzy Indexing and Retrieval in CBR with Weight Optimization Learning for Credit Evaluation

  • Park, Cheol-Soo;Ingoo Han
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2002년도 추계정기학술대회
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    • pp.491-501
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    • 2002
  • Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.

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러프집합이론과 사례기반추론을 결합한 기업신용평가 모형 (Integration rough set theory and case-base reasoning for the corporate credit evaluation)

  • 노태협;유명환;한인구
    • 한국정보시스템학회지:정보시스템연구
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    • 제14권1호
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    • pp.41-65
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    • 2005
  • The credit ration is a significant area of financial management which is of major interest to practitioners, financial and credit analysts. The components of credit rating are identified decision models are developed to assess credit rating an the corresponding creditworthiness of firms an accurately ad possble. Although many early studies demonstrate a priori which of these techniques will be most effective to solve a specific classification problem. Recently, a number of studies have demonstrate that a hybrid model integration artificial intelligence approaches with other feature selection algorthms can be alternative methodologies for business classification problems. In this article, we propose a hybrid approach using rough set theory as an alternative methodology to select appropriate attributes for case-based reasoning. This model uses rough specific interest lies in lthe stable combining of both rough set theory to extract knowledge that can guide dffective retrevals of useful cases. Our specific interest lies in the stable combining of both rough set theory and case-based reasoning in the problem of corporate credit rating. In addition, we summarize backgrounds of applying integrated model in the field of corporate credit rating with a brief description of various credit rating methodologies.

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상황인식 서비스의 안정적 운영을 위한 온톨로지 추론 엔진 선택을 위한 사례기반추론 접근법 (A Case-Based Reasoning Approach to Ontology Inference Engine Selection for Robust Context-Aware Services)

  • 심재문;권오병
    • 한국경영과학회지
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    • 제33권2호
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    • pp.27-44
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    • 2008
  • Owl-based ontology is useful to realize the context-aware services which are composed of the distributed and self-configuring modules. Many ontology-based inference engines are developed to infer useful information from ontology. Since these engines show the uniqueness in terms of speed and information richness, it's difficult to ensure stable operation in providing dynamic context-aware services, especially when they should deal with the complex and big-size ontology. To provide a best inference service, the purpose of this paper is to propose a novel methodology of context-aware engine selection in a contextually prompt manner Case-based reasoning is applied to identify the causality between context and inference engined to be selected. Finally, a series of experiments is performed with a novel evaluation methodology to what extent the methodology works better than competitive methods on an actual context-aware service.

사례기반 추론을 이용한 위험분석방법 연구 (A Study on Risk Analysis Methode Using Case-Based Reasoning)

  • 이혁로;안성진
    • 정보보호학회논문지
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    • 제18권4호
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    • pp.135-141
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    • 2008
  • 사이버 침해사고와 해킹의 위험성이 증대되고 있다. 이를 해결하기 위하여 정보보호기술중에서 보안위험분석 분야의 연구가 활발하게 이루어지고 있다. 하지만 평가를 위해서는 적지 않은 평가비용, 수개월의 평가기간, 평가 참여인원, 평가후의 보안대책비용, 보안관리비용에 대한 부담이 클 수밖에 없다. 이에 따라, 본 논문에서는 정량평가 형태의 위험분석평가를 프로젝트단위로 관리하며, 평가기간 및 적정 평가자 선정을 위한 사례기반추론알고리즘을 이용한 위험분석방법론 제안한다.

사례기반추론을 이용한 정보시스템 가치평가 모형개발에 관한 연구 (The Development of Value Evaluation Model of Information System using Case-Based Reasoning)

  • 박기남
    • 한국정보시스템학회지:정보시스템연구
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    • 제15권2호
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    • pp.95-123
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    • 2006
  • It is needed to evaluate information systems actively which has already developed to improve future performance of the organization and foster the activation of information system. The introduction or development of information system also can bring about a organizational success. To measure exactly the organizational performance of information systems, it is needed to develop a new valuation model for a specific information system from a objective pint of view, as well as to equip a standard methodology using BSC measurement. The information system valuation from a objective point of view is of importance as the basic information for the decision to obtain information system. This paper takes aim at investigating a new information system valuation model and developing a information system valuation system using case-based reasoning for predicting currency value of information system in each organization. A new information system valuation system is developed as a web-enabling base. Using this, users are able to estimate the value of specific information system on a real time efficiently.

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A Multistrategy Learning System to Support Predictive Decision Making

  • Kim, Steven H.;Oh, Heung-Sik
    • 재무관리논총
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    • 제3권2호
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    • pp.267-279
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    • 1996
  • The prediction of future demand is a vital task in managing business operations. To this end, traditional approaches often focused on statistical techniques such as exponential smoothing and moving average. The need for better accuracy has led to nonlinear techniques such as neural networks and case based reasoning. In addition, experimental design techniques such as orthogonal arrays may be used to assist in the formulation of an effective methodology. This paper investigates a multistrategy approach involving neural nets, case based reasoning, and orthogonal arrays. Neural nets and case based reasoning are employed both separately and in combination, while orthoarrays are used to determine the best architecture for each approach. The comparative evaluation is performed in the context of an application relating to the prediction of Treasury notes.

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Knowledge-Based Model for Forecasting Percentage Progress Costs

  • Kim, Sang-Yong
    • 한국건축시공학회지
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    • 제12권5호
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    • pp.518-527
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    • 2012
  • This study uses a hybrid estimation tool for effective cost data management of building projects, and develops a realistic cost estimation model. The method makes use of newly available information as the project progresses, and project cost and percentage progress are analyzed and used as inputs for the developed system. For model development, case-based reasoning (CBR) is proposed, as it enables complex nonlinear mapping. This study also investigates analytic hierarchy process (AHP) for weight generation and applies them to a real project case. Real case studies are used to demonstrate and validate the benefits of the proposed approach. By using this method, an evaluation of actual project performance can be developed that appropriately considers the natural variability of construction costs.

전문가시스템의 지원을 받는 블럭분할 CAPP 시스템 (A Block Division CAPP System Supported by Expert System)

  • 이재원;황인식;이용재
    • 대한조선학회논문집
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    • 제32권3호
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    • pp.44-50
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    • 1995
  • 본 연구는 선체 블럭분할 작업을 지원하는 CAPP(computer aided process planning) 시스템 개발에 관한 것이며, 시스템 명은 BLOCK 이다. 시스템의 구성은 블럭분할선을 생성하는 전문가시스템과, 블럭분할선의 평가와 편집을 할 수 있는 분할 평가 및 수정 시스템으로 이루어져 있다. 전문가시스템의 추론 기법으로는 사례기반추론(case-based reasoning)기법을 이용하였다. 블럭분할선은 분할선 편집기에서 그래픽적으로 편집할 수 있고, 만족도 평가는 별도의 평가표 윈도우 상에서 할 수 있다. 전문가시스템은 웍스테이션 상에서 전문가시스템 개발 도구인 NEXPERT Object를 사용하여 개발하였다. 본 연구에서의 대상 선종은 VLCC이다.

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