• 한국지능시스템학회논문지
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• 제13권3호
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• pp.366-370
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• 2003

In this research, we suggest a hybrid intelligent Web recommendation systems based on Web data mining and case-based reasoning (CBR). One of the important research topics in the field of Internet business is blending artificial intelligence (AI) techniques with knowledge discovering in database (KDD) or data mining (DM). Data mining is used as an efficient mechanism in reasoning for association knowledge between goods and customers＇ preference. In the field of data mining, the features, called attributes, are often selected primary for mining the association knowledge between related products. Therefore, most of researches, in the arena of Web data mining, used association rules extraction mechanism. However, association rules extraction mechanism has a potential limitation in flexibility of reasoning. If there are some goods, which were not retrieved by association rules-based reasoning, we can＇t present more information to customer. To overcome this limitation case, we combined CBR with Web data mining. CBR is one of the AI techniques and used in problems for which it is difficult to solve with logical (association) rules. A Web-log data gathered in real-world Web shopping mall was given to illustrate the quality of the proposed hybrid recommendation mechanism. This Web shopping mall deals with remote-controlled plastic models such as remote-controlled car, yacht, airplane, and helicopter. The experimental results showed that our hybrid recommendation mechanism could reflect both association knowledge and implicit human knowledge extracted from cases in Web databases.

• 한국경영과학회지
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• 제28권3호
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• pp.135-148
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• 2003

In this paper we introduce the Internet-based purchase support systems using data mining and case-based reasoning (CBR). Internet Business activity that involves the end user is undergoing a significant revolution. The ability to track users browsing behavior has brought the vendor and end customer's closer than ever before. It is now possible for a vendor to personalize his product message for individual customers at massive scale. Most of former researchers, in this research arena, used data mining techniques to pursue the customer's future behavior and to improve the frequency of repurchase. The area of data mining can be defined as efficiently discovering association rules from large collections of data. However, the basic association rule-based data mining technique was not flexible. If there were no inference rules to track the customer's future behavior, association rule-based data mining systems may not present more information. To resolve this problem, we combined association rule-based data mining with CBR mechanism. CBR is used in reasoning for customer's preference searching and training through the cases. Data mining and CBR-based hybrid purchase support mechanism can reflect both association rule-based logical inference and case-based information reuse. A Web-log data gathered in the real-world Internet shopping mall is given to illustrate the quality of the proposed systems.

• 셀메드
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• 제14권2호
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• pp.4.1-4.4
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• 2024

The development of clinical reasoning, which is the basis of medical education, is of great importance in medical universities. One of the founders of modern structural clinical reasoning, based on the knowledge of pathological physiology, is the inventor of the stethoscope Rene Laennec (1781-1826). He described the pioneering experience of clinical reasoning in the pages of his treatise A Treatise on the Diseases of the Chest and on Mediate Auscultation, which is of lasting value, since every rookie physicians in his professional development goes through the path of Laennec. Laennec's practice is of great importance for novice physicians since Laennec's treatise contains a diagnostic analysis of the most common clinical cases. Each such analysis demonstrates the algorithm of clinical reasoning. The purpose of this study was to analyze the approaches of clinical reasoning by René Laennec, which made it possible to identify two basic principles. Laennec's diagnostic reasoning involved two principles: pathogenetic analysis of clinical manifestations and a syndrome-based approach to differential diagnosis. These principles help distinguish between diseases with similar symptoms and physical findings are used to demonstrate the practical application of syndrome-based differential diagnosis. These principles can be easily mastered by understanding the pathogenesis of clinical manifestations. Thanks to the pathogenetic basis, the principles of clinical reasoning of Rene Laennec are universal and applicable to the analysis of any signs of the disease: not only physical but also laboratory and instrumental.

• The Journal of Asian Finance, Economics and Business
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• 제7권2호
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• pp.221-228
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• 2020

This study suggests an alternative to the conventional collaborative filtering method for predicting consumer choice, using case-based reasoning. The algorithm of case-based reasoning determines the similarity between the alternative sets that each subject chooses. Case-based reasoning uses the inverse of the normalized Euclidian distance as a similarity measurement. This normalized distance is calculated by the ratio of difference between each attribute level relative to the maximum range between the lowest and highest level. The alternative case-based reasoning based on similarity predicts a target subject's choice by applying the utility values of the subjects most similar to the target subject to calculate the utility of the profiles that the target subject chooses. This approach assumes that subjects who deliberate in a similar alternative set may have similar preferences for each attribute level in decision making. The result shows the similarity between comparable alternatives the consumers consider buying is a significant factor to predict the consumer choice. Also the interaction effect has a positive influence on the predictive accuracy. This implies the consumers who looked into the same alternatives can probably pick up the same product at the end. The suggested alternative requires fewer predictors than conjoint analysis for predicting customer choices.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2009년도 춘계 종합학술대회 논문집
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• pp.74-78
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• 2009

온톨로지가 대용량화되면서 온톨로지 시스템의 성능 향상을 위해 효율적인 추론이 중요해졌다. 본 논문에서는 DBMS 기반의 온톨로지 저장소에서 RDFS 포함관계 함의 규칙 (rdfs7 규칙과 rdfs9 규칙)과 OWL 역관계 규칙(owl:inverseOf)의 추론을 효율적으로 수행할 수 있는 방법으로서, DB 테이블에 대한 뷰(view)를 활용하는 방법을 소개한다. 추론 규칙을 뷰 정의로 대체하고 RDF 트리플을 구조화된 트리플 테이블에 저장하는 것으로 추론이 완료되며 대신 질의 처리과정에서는 그 뷰를 참조하면 된다. 이와 같이 뷰를 정의하는 것으로 추론을 대신함에 따라 추론에 소요되는 시간을 단축할 수 있고 트리플 저장소의 공간 효율성도 얻을 수 있다.

• 한국가정과교육학회지
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• 제12권3호
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• pp.115-127
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• 2000

The purpose of this study is to develop lesson plans. teaching guide, and teaching materials applying practical reasoning teaching model in the area of ’human development and family relationship’in middle school home economics. The practical reasoning teaching model consists of five factors: Desired results, Awareness of context, Alternative approaches, Consequences of action, and Action. This study based on practical reasoning has following process: Curriculum development. Developing lesson pan, teaching material, an teaching guide, Experimental teaching and evaluation. Feedback, Production of CD-Rom. Teaching guide includes lesson plan, workbook multimedia materials and teaching resources. Especially teaching guide in CD-Rom can be used effectively in the actual teaching. In the classroom, this teaching model accomplished active and interesting participation of teachers and students. It is proposed that practical reasoning teaching model should be applied to other areas of home economics. In addition various teaching materials based on practical reasoning need to developed.

• 한국과학교육학회지
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• 제38권5호
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• pp.599-610
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• 2018

이 연구의 목적은 파브르의 탐구 과정에서 나타난 메커니즘 추론을 분석하고, 분석 결과에 기반하여 메커니즘 추론 모델을 개발하는 것이다. 이를 위해 Russ et al.(2008)의 분석틀을 수정 보완한 메커니즘 추론 분석틀로 "파브르 곤충기 1~10" 가운데 추론요소가 등장하는 30개의 챕터를 분석하였다. 분석결과 첫째, 파브르의 탐구 과정에서 나타난 메커니즘 추론의 하위 과정 요소는 선지식확인, 대상속성확인, 시작조건확인, 활동확인 등의 과정이 반복적으로 일어났다. 뿐만 아니라 이 메커니즘 추론의 과정 요소들의 순서는 탐구 주제, 의문 유형, 선지식이나 주어진 상황 등에 따라 다르게 나타났으며, 비선형적이고 반복적인 형태로 나타났다. 둘째, 메커니즘 추론의 과정 요소가 나타난 순서에 기반하여 메커니즘 추론 모델을 개발하였다. 파브르의 탐구 과정 분석을 통해 제안되는 메커니즘 추론 모델은 실체확인형 메커니즘 추론 모델(MIE), 활동확인형 메커니즘 추론 모델(MIA), 실체 속성확인형 메커니즘 추론 모델(MIP) 3가지였다. 이러한 결과는 인과 메커니즘을 밝히고자 하는 탐구를 수행하는 학생들에게 교사가 Why 뿐만 아니라 How, If, What과 같은 다양한 발문을 통해 탐구를 진행하도록 유도할 수 있음을 시사해준다. 또한 교사는 자연 현상의 기저에 존재하는 여러 실체들을 인식하는 메커니즘적 이해가 요구되며 학생들에게 다양한 가설을 생성하도록 하는 기회를 제공해야함을 시사해 준다.

• 한국과학교육학회지
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• 제14권2호
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• pp.133-142
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• 1994

Many students have misconceptions that upward direction force act on the object which is moving upward after being thrown vertically upward, and no force act on the object at the top of its flight because the object stop or don't' move at the top. To change these misconceptions, in this study, deductive reasoning tasks were used, and student's responses to the tasks were analyzed. In the first part of this study, student's prior conceptions about force and motion and student's deductive reasoning abilities were investigated. And the second part, student's explanations were classified to either the premise-based or idea-based explanation. In the case of the object which is moving upward, 62% of students who had misconception changed their misconceptions to physically correct concept, but, only 24% of students changed their misconceptions for the object at the top. For the first task, more students changed their misconceptions when they made responses based on premises than based on their own idea(p<.05), so, the first task can be helpful for conceptual change. 40% students changed their own misconception by reasoning deductively based on premises provided in the first task, but only 17% students changed by the second task. Student's reasoning abilities investigated in the first part of this study did not affect the conceptual change. Four students for the first task and one student for the second task did not change their misconception even though they made premise-based explanation and had high reasoning abilities.

• 아동학회지
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• 제26권2호
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• pp.1-14
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• 2005

This study investigated moral judgment and moral reasoning about aggressive behavior by intention, presentation of results of aggressive behavior, and age of child. Forty-four 3-year old and forty-six 5-year-old day-care children in Seoul and Kyonggi Province were interviewed individually with 20 pictorial tasks. Data analysis was by frequencies, percentiles, means, standard deviations, paired t-test, and ANOVA(repeated measures). Both age groups judged instrumental and resentment-based types of aggression to be worse than prosocial or rule observance-based aggression. Both age groups judged aggressive behavior to be worse when results of aggression were presented. Five-year-olds judged aggression to be worse on instrumental than on retributive types of intent. Level of reasoning on aggressive behavior was lowest in cases of satisfying resentment Level of reasoning about aggression increased with age.

• 한국콘텐츠학회논문지
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• 제1권1호
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• pp.51-58
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• 2001

전자상거래 시스템은 편리한 인터페이스와 상품 정보에 대해 고객이 만족할 만한 수준의 쉽고 빠른 검색 기능을 제공 하여야한다. 이를 위해 지능형 에이전트 기술을 이용한 전자상거래 시스템에 대한 연구가 활발히 진행 되고 있다. 본 논문에서는 혼합적 추론 방법을 이용하여 전자상거래 고객의 요구를 좀더 충실히 반영한 상품의 정보와 고객의 관리가 가능하도록 한 전자상거래 에이전트 시스템을 설계하였다. 본 논문에서는 전자상거래 시스템의 효율을 높이기 위하여 먼저 에이전트는 지식기반의 지능적 다중에이전트로서 사례를 기반으로 한 사례기반 추론과 규칙을 기반으로 한 규칙기반 추론의 단점을 보완한 혼합적 추론 기법을 이용하였다. 또한 동시에 발생하는 다중 사용자의 응답 속도 저하를 방지하기 위해 메인 서버에서 로드 밸런싱을 통한 로드의 분산 기법과 2-계층 구조의 에이전트 구조를 통해 네트워크의 트래픽을 분산시킨 시스템을 설계하였다. 본 논문에서 제안한 전자상거래 시스템은 고객의 다양한 요구에 대한 적응성을 높였고 시스템에 대해 동시에 발생하는 다중 사용자의 요구로 인한 응답 속도의 저하를 막을 수 있다.