• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.121-124
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• 2003

It is a major concern of e-shopping mall managers to satisfy a variety of customer's desire by recommending a proper commodity to the expected purchaser. Customer information like customer's fondness and idiosyncrasy in shopping has not been used effectively for the customers or the suppliers. Conventionally, e-shopping mall managers have recommended specific items of commodities to their customers without considering thoroughly in a customer point of view. This study introduces the ways of a choosing and recommending of commodities for customer themselves or others. A similarity measure between one member's idiosyncrasy and the other members' is developed based on the rule base and the case base. The case base is improved by recognizing and learning the changes of customer's desire and shopping trend.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.30
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• pp.161-165
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• 1994

The shipbuilding industry is one of the domains which need an effective computer application. Particularly the productivity of process planning of a shipbuilding for crude -oil tanker can be greatly enhanced by introducing CAPP(Computer Aied Process Planning). In this paper we describe a prototype expert system which enables block division process planning in shipbuilding. The system determines block division lines of the midship sections of oiltanker. Case-based reasoning(CBR) approach is applied for this purpose instead of rule-based one.

• IE interfaces
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• v.21 no.4
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• pp.411-417
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• 2008

An impeller is a type of high-speed rotor that is used to compress or transfer fluid under high-speed and pressure at high temperatures. The impeller is composed of an axial hub and several blades attached along the hub. The weight and shape of an impeller must be balanced, because their imbalances can cause noise and vibration, which can lead to the breakage of the impeller blades during operation. Thus, the hub and blades of an impeller are commonly machined in a 5-axis NC machine to obtain qualified surfaces. The impeller machining strategy or process plan can not be easily obtained due to the complex, overlapped and twisted shapes of impeller blades. Skillful machining process planners may generate appropriate machining strategies based on their experiences and floor data. However, in practice most shop floor data for the impeller machining is not well-structured such that it does not effectively provide a process planner with information for machining strategies and/or process plans. This paper reports the development of a case-based machining strategy support system (CBMS) that employs case-based reasoning to obtain the machining strategy of an impeller by using the existing machining strategies of the shop floor. The CBMS generates impeller machining strategies through a stepwise reasoning process considering the similarity features between the blade shapes and machining regions. A case study is provided to demonstrate that CBMS can generate useful machining strategies facilitating process planners. The developed system can simulate the tool paths of impeller machining and runs on the web.

• Architectural research
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• v.17 no.2
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• pp.57-64
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• 2015

In architectural planning, previous cases of similar spatial program provide important data for architectural design. Case-based reasoning (CBR) paradigm in the field of architectural design is closely related to the designing behavior of a planner who makes use of similar architectural designs and spatial programs in the past. In CBR, spatial graph can be constituted with most fundamental data, which can provide a method of searching spatial program by using visual graphs. This study developed a system for CBR that can analyze the similarity through graph comparison and search for buildings. This is an integrated system that is able to compare space similarity of different buildings and analyze their types, in addition to the analysis on a space within a single structure.

• Korean Journal of Construction Engineering and Management
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• v.9 no.6
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• pp.257-267
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• 2008

In order to encourage construction practitioners to acknowledge failures and disseminate the information, the failure information must be documented and accumulated with a well-structured format, which contains not only the fact and result but also the circumstance and cause of the failure. In the Korean construction industry, many failures are not explained clearly and often not even reported publicly, partly because due to the lack of understanding positive aspects of failures, which can improve construction practices as a result of learning from failures. The purpose of this study is to develop a web-based construction failure information system using the case-based reasoning techniques, which can systematically accumulate, manage, and share the valuable failure information using a structured failure cases database. It can be utilized for planning proactive solutions on future failures by searching the very similar past failure cases.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.14-18
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• 2002

전자상거래가 점차 활성화됨에 따라 다양한 형태의 쇼핑몰들이 구축되고 있으나, 구매자가 상품을 구입하는데 있어 구매자 기호와 요구에 적합한 상품을 검색하기에는 미흡한 실정이다. 따라서, 본 논문에서는 CBR(Case Based Reasoning)과 RBR(Rule Based Reasoning)을 통합한 검색에이전트와 사용자 프로파일과 선호도를 관리하는 사용자 에이전트로 이루어진 멀티 에이전트를 이용하는 CARUBA 시스템을 설계하고, 검색에이전트가 사용자에이전트에서 보낸 정보를 이용하여 유사도를 산출하여 구매자의 요구에 적합한 상품을 신속하게 추천할 수 있는 방법을 제안한다

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.91-109
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• 2004

This study investigates the effectiveness of a hybrid approach using fuzzy sets that describe approximate phenomena of the real world. Compared to the other existing techniques, the approach handles inexact knowledge in common linguistic terms as human reasoning does it. Integration of fuzzy sets with case-based reasoning (CBR) is important in that it helps to develop a successful system far dealing with vague and incomplete knowledge which statistically uses membership value of fuzzy sets in CBR. The preliminary results show that the accuracy of the integrated fuzzy-CBR approach proposed for this study is higher that of conventional techniques. Our proposed approach is applied to corporate bond rating of Korean companies.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.96-106
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• 1999

Case-Base Reasoning(CBR) solves the new problems by reusing the solutions to previously solved problems. But, there are differences between previously known case and a new problems. To solve this problem Case-Based System have to adapt the solution of the case to suit a new situation. In current CBR systems, case adaptation is usually performed by rule-based method that use rules hand-coded by the system developer. So, CBR system designer faces knowledge acquisition bottleneck akin to those found in traditional expert system design. To solve this problem, in this thesis, we present an automatic learning method of case adaptation knowledge using case base, we use a method of comparing cases in the case base to learn adaptation knowledge. The system is tested in the domain for the decision of travel-price. The result shows accuracy improvement in comparison with case retrieval-only system.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.241-246
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• 2004

The importance of electronic commerce system has been growing rapidly due to development of information technology and acceleration of enterprise e-business. Electronic commerce system must provide convenient interface, easy and fast searching function, and product information satisfied customer's. A study about the system that used a reasoning technique and an Agent technology for this is required. In this paper, we designs electronic commerce system with customer preference and sales agent which is composed of case-based reasoning and rule-based reasoning for high customer satisfaction. Also, we were shown on an appropriateness of a proposal system by an experiment.

• Journal of Intelligence and Information Systems
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• v.3 no.1
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• pp.31-45
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• 1997

To date, research on data mining has focused primarily on individual techniques to su, pp.rt knowledge discovery. However, the integration of elementary learning techniques offers a promising strategy for challenging a, pp.ications such as forecasting nonlinear processes. This paper explores the utility of an integrated a, pp.oach which utilizes a second-order learning process. The a, pp.oach is compared against individual techniques relating to a neural network, case based reasoning, and induction. In the interest of concreteness, the concepts are presented through a case study involving the prediction of network traffic for video-on-demand.