• 대한산업공학회지
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• 제41권2호
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• pp.150-161
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• 2015

This paper proposes a new approach to technology valuation, the market-replacement cost approach which integrates the cost-based approach and market-based approach. The proposed approach estimates the market-replacement cost of a target technology using R&D costs of similar R&D projects previously conducted. Similar R&D projects are extracted from project database based on document similarity between project proposals and technology description of the target technology. R&D costs of similar R&D projects are adjusted by mirroring the rate of technological obsolescence and inflation. Market-replacement cost of the technology is then derived by calculating the weighted average of adjusted costs and similarity values of similar R&D projects. A case of "Prevention method and system for the diffusion of mobile malicious code" is presented to illustrate the proposed approach.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 춘계학술대회 논문집
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• pp.370-374
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• 1993

This paper describes a study on the expert system based process planning of the block division process in shipbuilding. The prototype system developed deterines the block division line of the midship of crude-oil tanker. Case-based reasoning (CBR) approach relying on previous similar cases to solve the problem is applied instead of rule-based reasoning (RBR). Similar cases are retrieved from case base according to the similarity metrics between input problem and cases. The retrieved case with the highest priority is then adapted to fit to the input problem buy adaptation rules. The adapted solution is proposed as the division line for the input problem.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2003년도 춘계학술대회
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• pp.474-483
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• 2003

A number of studies for corporate bond rating classification problems have demonstrated that artificial intelligence approaches such as Case-based reasoning (CBR) can be alternative methodologies to statistical techniques. CBR is a problem solving technique in that the case specific knowledge of past experience is utilized to find a most similar solution to the new problems. To build a successful CBR system to deal with human information processing, the representation of knowledge of each attribute is an important key factor We propose a hybrid approach of using fuzzy sets that describe the approximate phenomena of the real world because it handles inexact knowledge represented by common linguistic terms in a similar way as human reasoning compared to the other existing techniques. Integration of fuzzy sets with CBR is important to develop effective methods for dealing with vague and incomplete knowledge to statistical represent using membership value of fuzzy sets in CBR.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2003년도 추계학술대회 및 정기총회
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• pp.201-204
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• 2003

A hybrid artificial intelligence approach based on combining case based reasoning and neural networks is presented. The approach is designed to allow for solving blowing control of BOF(basic oxygen furnace), example of which lie at the core of steelmaking process control systems application in the steel industry. According to this hybrid approach, the system, when faced with a new problem, first retrieves similar cases and neural network is used to solve the problem. Experimental Results indicate that combining case based reasoning and neural network offers an efficient approach to solving control and prediction problem

• 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.

• 대한음성학회지:말소리
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• 제58호
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• pp.45-66
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• 2006

In this paper, a rule-based (transformation-based) NE recognition system is proposed. This system uses Brill's rule inference approach. The performance of the rule-based system and IdentiFinder, one of most successful stochastic systems, are compared. In the baseline case (no punctuation and no capitalisation), both systems show almost equal performance. They also have similar performance in the case of additional information such as punctuation, capitalisation and name lists. The performances of both systems degrade linearly with the number of speech recognition errors, and their rates of degradation are almost equal. These results show that automatic rule inference is a viable alternative to the HMM-based approach to NE recognition, but it retains the advantages of a rule-based approach.

• 지능정보연구
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• 제9권1호
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• pp.23-51
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• 2003

인터넷 쇼핑몰에서 사례기반추론기법을 통한 유사상품의 탐색과 사용자 요구에 적합한 상품추천을 위해서는 다양한 요구에 부응할 수 있는 사례베이스의 구축이 우선되어야 한다. 그리고 구축된 사례베이스로부터 유사한 사례를 검색하여 재 사용하거나 필요시 수정하고, 그 결과를 다시 저장하는 기능이 요구된다. 사례기반 상품추천시스템 개발에 있어 가장 중요한 요소는 사례의 표현문제이다. 본 연구에서는 인터넷 수산물 쇼핑몰의 상품추천시스템에서 번들상품 구성문제(집안 이벤트 시 필요한 수산물의 집합)를 표현하는데 적합한 사례표현기법을 개발하며, 유사사례를 추출하기 위한 유사도 척도의 개발에 연구의 첫 번째 주안점을 둔다. 본 논문에서는 번들상품추천을 위한 사례표현기법으로 객체모델링(OMT)기법을 사용하고 있다. 또한 다양한 사례 속성 유사도 측정방법을 적용하며, 유사도 측정에서 분류법(taxonomy)의 의미와 그 적용방법을 제시한다.

• Asia pacific journal of information systems
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• 제25권4호
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• pp.626-641
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• 2015

Conventional case-based reasoning (CBR) does not perform efficiently for high-volume datasets because of case retrieval time. To overcome this problem, previous research suggested clustering a case base into several small groups and retrieving neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performance than the conventional CBR. This paper proposes a new case-based reasoning method called the clustering-merging CBR (CM-CBR). The CM-CBR method dynamically indexes a search pool to retrieve neighbors considering the distance between a target case and the centroid of a corresponding cluster. This method is applied to three real-life medical datasets. Results show that the proposed CM-CBR method produces similar or better predictive performance than the conventional CBR and clustering-CBR methods in numerous cases with significantly less computational cost.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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• pp.355-361
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• 1999

An application of case-based reasoning is proposed to build an influence diagram for identifying successful new ventures. The decision to invest in new ventures in characterized by incomplete information and uncertainty, where some measures of firm performance are quantitative, while some others are substituted by qualitative indicators. Influence diagrams are used as a model for representing investment decision problems based on incomplete and uncertain information from a variety of sources. The building of influence diagrams needs much time and efforts and the resulting model such as a decision model is applicable to only one specific problem. However, some prior knowledge from the experience to build decision model can be utilized to resolve other similar decision problems. The basic idea of case-based reasoning is that humans reuse the problem solving experience to solve a new decision. In this paper, we suggest a case-based reasoning approach to build an influence diagram for the class of investment decision problems. This is composed of a retrieval procedure and an adaptation procedure. The retrieval procedure use two suggested measures, the fitting ratio and the garbage ratio. An adaptation procedure is based on a decision-analytic knowledge and decision participants knowledge. Each step of procedure is explained step by step, and it is applied to the investment decision problem in new ventures.

• 한국안전학회지
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• 제14권1호
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• pp.167-176
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• 1999

Construction accidents occur reiteratively in similar fashions. There have been several attempts to develop a safety program for preventing construction accidents on sites. It will be very effective to use previous accident cases for establishing proper safety plan and managing safety process. This research develops a case-based construction safety management system which enables construction managers or safety managers to prevent potential accidents during the construction process. The case-oriented approach is performed through the representation of previous accident cases in accordant with the similarity to the conditions of current site. It uses a case-based reasoning which is one of the reasoning methods of an expert system. A prototype system for the reasoning model was implemented using one of the case based system development tools. The system was applied to a real construction site to verify its capability and validity. It was founded that the causes of accidents were successfully removed, so the proposed model proved to be reasonable. Additional research is needed to resolve the technical problem how to adapt the countermeasures for accident prevention provided by the reasoning model.