• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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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.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 1999.06a
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• pp.223-228
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• 1999

This paper presents an electrical fire diagnosis system using intellectual reasoning which is the mixed approach of the case-based reasoning with the knowledge-based reasoning A prototype system is implemented using Delphi, one of the program development tools under windows environment, for making an application program for database. And database is builded using Paradox. The results of applying the system to some imaginary fire cases to verify its capability and validity show that the causes of fires is successfully diagnosed, so the proposed system proves to be reasonable.

• Information Systems Review
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• v.16 no.1
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• pp.37-50
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• 2014

Conventional case-based reasoning (CBR) does not perform efficiently for high volume dataset because of case-retrieval time. In order to overcome this problem, some previous researches suggest clustering a case-base into several small groups, and retrieve neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performances than the conventional CBR. This paper suggests a new hybrid case-based reasoning method which dynamically composing a searching pool for each target case. This method is applied to diagnose for the heart disease dataset. The results show that the suggested hybrid method produces statistically the same level of predictive performances with using significantly less computational cost than the CBR method and also outperforms the basic clustering-CBR (C-CBR) method.

• Journal of Korean Elementary Science Education
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• v.37 no.4
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• pp.372-390
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• 2018

The purpose of this research is to know the scientific reasoning ability of elementary students. In order to find it, 320 elementary students wrote a report about germination of the 700 or 2,000 years old seeds. Their writings were analyzed by scientific writing analysis frameworks, Scientific Reasoning Types and Scientific Reasoning Level Criteria developed by Lim (2018). Minto Pyramid Principles was used to show statements and relations of statements related to scientific reasoning. This paper showed scientific reasoning statements of elementary students about germination of seeds. The characteristics of scientific reasoning of elementary students were as follows. In the process of logical writing by the types of scientific reasoning, many students showed various characteristics and different levels. In the writings based on inductive reasoning, they did not distinguish between common features and differences of cases, and did not derive the rules based on common features and differences of the cases. In the writings based on deductive reasoning, there were cases where the major premise corresponding to the principle or rule was omitted and only the phenomenon was described, or the rule was presented but not connected with the case. In the writings based on abductive reasoning, the ability to selectively use the background knowledge related to the question situation was not sufficient, and borrowing of similar background knowledge, which was commonly used in other situations, was very rare.

• IE interfaces
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• v.23 no.1
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• pp.48-57
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• 2010

A tryout is one of the most important process in development and production of dies. For automotive press dies, it takes 3 to 4 months during the vehicle development process. Moreover, useful information and knowledge from tryout process is very important to design and production planning of dies. In this paper, we developed a new supporting system for making and managing tryout reports of an automotive press die. The CBDTS(Case-Based reasoning for Die Tryout report System) was developed and applied using case-based reasoning method in order to reduce time and manage knowledge of tryout. It consists of "Class Retrieval Wizard", "Case Cleansing Module", and "Case Viewer." Also, this CBDTS could be a channel to integrate field information with enterprise-wide information management systems as well. The CBDTS was applied to a Korean automotive press die shop, and the results were very satisfied in both quantitative and qualitative manners.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.48-53
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• 2010

In this paper, we develop the intelligent remote dust chamber bag control system which is combination of the advanced IT and traditional dust chamber based on event. At first, the message format is defined for the efficient dust chamber bag information transmission using power line communication. Also, we define the data types to logically model the dust chamber and the dust chamber bag, and they are logically modeled using XML and object-oriented modeling method. In addition to, we apply the case-based reasoning for showing the dust chamber bag exchange time intelligently to user at real-time using casebase, that is collected by case or case-based reasoning result, and that is described using XML.

• Journal of the Korea Institute of Building Construction
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• v.12 no.2
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• pp.133-141
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• 2012

As we move from the industrial age to the information age, domestic industries are changing rapidly, and rural society is also laying the foundation to make use of information technologies. Through this kind of modernization, the size of agricultural facilities has been increasing on a significant scale. But, in reality, there are many difficulties in the maintenance of agricultural facilities in proportion to their growing number. Accordingly, this research aims to solve the fundamental problems that occur with agricultural facilities in the maintenance stage. In addition, it aims to provide information on how to maintain and manage facilities for farmers. The presentation of the maintenance information was conducted using a case-based reasoning method that solves current problems based on past cases. The tool of case-based reasoning was applied to define the establishment of the base for cases, characteristic variables and maintenance measures. The effectiveness of a CBR model was examined through the case study. The use of the case-based reasoning method is judged to be effective as a tool to support the decisions of farmers regarding maintenance. When the maintenance measures derived through the CBR model are offered to farmers, the fundamental problems of maintaining agricultural facilities will be solved, and the damage to such facilities minimized.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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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.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.189-192
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• 2004

The present much information of internet has to exist for innumerable user so that couldn't satisfy there's a variety of demand. so they have a demerit that search unnecessary information. However Web service is different with other mass media because It is possible that enable Mass Customization for Personalization strategy. In The paper suggest reasoning system that detect user connection location by using indirect abstraction techniques a kind of Case-based reasoning techniques.

• Journal of Intelligence and Information Systems
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• v.3 no.2
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• pp.33-55
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• 1997

A data model is a diagram that describes the properties of different categories of data and the associations among them within a business or information system. In spite of its importance and usefulness, data modeling activity requires not only a lot of time and effort but also extensive experience and expertise. The data models for similar business areas are analogous to one another. Therefore, it is reasonable to reuse the already-developed data models if the target business area is similar to what we have already analyzed before. In this research, we develop a case-based reasoning system for data model reuse, which we shall call CB-DM Reuser (Case-Based Data Model Reuser). CB-DM Reuse consists of four subsystems : the graphic user interface to interact with end user, the data model management system to build new data model, the case base to store the past data models, and the knowledge base to store data modeling and data model reusing knowledge. We present the functionality of CB-DM Reuser and show how it works on real-life a, pp.ication.