• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.3
• /
• pp.366-370
• /
• 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.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.28 no.3
• /
• pp.135-148
• /
• 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.

• CELLMED
• /
• v.14 no.2
• /
• pp.4.1-4.4
• /
• 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
• /
• v.7 no.2
• /
• pp.221-228
• /
• 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.

• Proceedings of the Korea Contents Association Conference
• /
• 2009.05a
• /
• pp.74-78
• /
• 2009

Efficient reasoning has become important for improving the performance of ontology systems as the size of ontology grows. In this paper, we introduce a method that efficiently performs reasoning of RDFS entailment rules (i.e., rdfs7 and rdfs9 rules) and OWL inverse rule using views in the DBMS-based triple sotre. Reasoning is performed by replacing reasoning rules with the corresponding view definition and storing RDF triples into the structured triple tables. When processing queries, the views is referred instead of original tables. In this way, we can reduce the time needed for reasoning and also obtain the space-efficiency of the triple store.

• Journal of Korean Home Economics Education Association
• /
• v.12 no.3
• /
• pp.115-127
• /
• 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.

• Journal of The Korean Association For Science Education
• /
• v.38 no.5
• /
• pp.599-610
• /
• 2018

The purpose of this study is to analyze mechanistic reasoning in Fabre's inquires and to develop mechanistic reasoning model. To analyze the order of the process elements in mechanistic reasoning, 30 chapters were selected in book. Inquiries were analyzed through a framework which is based on Russ et al. (2008). The nine process elements of mechanistic reasoning that was presented in Fabre's inquires were as follows: Describing the Target Phenomenon, Identifying prior Knowledge, Identifying Properties of Objects, Identifying Setup Conditions, Identifying Activities, Conjecturing Entities, Identifying Properties of Entities, Identifying Entities, and Organization of Entities. The order of process elements of mechanistic reasoning was affected by inquiry's subject, types of question, prior knowledge and situation. Three mechanistic reasoning models based on the process elements of mechanistic reasoning were developed: Mechanistic reasoning model for Identifying Entities(MIE), Mechanistic reasoning model for Identifying Activities(MIA), and Mechanistic reasoning model for Identifying Properties of entities (MIP). Science teacher can help students to use the questions of not only "why" but also "How", "If", "What", when students identify entities or generate hypotheses. Also science teacher should be required to understand mechanistic reasoning to give students opportunities to generate diverse hypotheses. If students can't conjecture entities easily, MIA and MIP would be helpful for students.

• Journal of The Korean Association For Science Education
• /
• v.14 no.2
• /
• pp.133-142
• /
• 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.

• Korean Journal of Child Studies
• /
• v.26 no.2
• /
• pp.1-14
• /
• 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.

• The Journal of the Korea Contents Association
• /
• v.1 no.1
• /
• pp.51-58
• /
• 2001

Electronic commerce system must provide convenient interface, easy and fast searching function, and production information satisfying customers. To do this, many kinds of studies are being advanced actively about electronic commerce system using intelligent agent electronic This paper suggests 2-tier electronic commerce system using intelligent multi agent. We propose a combined reasoning agent system which provides production information satisfying customer's needs using both case-based reasoning and rule-based reasoning. And this system distribute network and sewer system load based on load balancing and 2-tier agent structure. This system can find production information through teaming of rule-based reasoning method and case-based reasoning method. This system can provide the best suitable production information to customers by using combined reasoning agent system. And we can prevent customer's unexpected long waiting causes by network traffic and server load.