• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.268-273
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• 2000

기존의 웹 기반 학습 평가 시스템은 학습자의 선택 기회가 없는 상태에서 일방적으로 제시된 문제지로 평가하게 되거나, 문제 은행에서 임의로 추출한 문제도 단순히 무작위로나 난이도만을 고려하여 문제지를 구성하였고, 그 결과에 대한 성취도의 분석도 한 문제지에 대한 정오표 또는 점수로 단순하게 제시하기 때문에 학습자의 지속적인 학습 관리가 이루어지지 못하고 있다. 본 논문에서는 문제유형, 과목 및 단원 난이도, 문항 형태, 문항당 배점, 문항당 배당 시간등의 다양한 정보를 가진 유형별 문제 은행을 구축하였다. 학습자는 마치 문제집을 풀고 싶은 유형의 문제를 선택하듯이 문제 은행에서 문제를 자율적으로 구성하여 평가할 수 있는 유형별 문제지나 대학수학능력시험의 기준에 맞추어 자동 구성되는 종합 문제지로 다양하게 평가할 수 있다. 또한, 한문제지에 대한 결과뿐만 아니라 유형별, 월별 성취도 분석을 통하여 평가한 총점에 대한 획득한 점수의 누적 통계를 그래프로 일목요연하게 보여주어 한 학습자에 대한 지속적인 성취도 분석이 가능하도록 구축하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.505-507
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• 2004

최근 웹 서비스 사용자와 웹상에 대용량 콘텐츠의 급증으로 웹 서버의 부하가 가중되고 서비스의 질이 떨어지는 문제가 발생하였다. 이러한 문제의 해결로 콘텐츠를 다수의 지역 서버에 복제하고 복제 서버로 하여금 클라이언트의 요청을 처리하도록 하여 웹 서버의 부하를 줄이고 트래픽을 분산하는 콘텐츠 분산 네트워크 기술이 사용되고 있다. 이러한 다수의 복제 서버 사용하는 환경에서는 복제 서버의 효용을 극대화 할 수 있는 배치 전략이 필요하다. 본 논문에서는 복제 서버의 효율을 위하여 선형 구조상에서 지연과 트래픽이 기반 한 각 노드의 비용이 임계값을 초과하지 않도록 복제 서버를 배치할 수 있는 방안을 제시하여 O(N(N-1))의 시간복잡도로 문제를 해결하였다.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.437-442
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• 2003

최근 마그네틱 카드에 의한 금융 피해가 심각한 사회적 문제로 대두되고 있다. 이것이 복제가 쉬운 마그네틱 카드인 것이 첫번째 문제이고 더 더욱 중요한 것은 현재와 같은 ID와 패스워드 방식으로는 온라인 신용사회 구축에 큰 문제가 발생할 수 있다는 것이다. 이를 해결키 위해서는 생체학적 또는 행동학적 특징을 통한 본인 여부를 확인시켜 줄 수 있는 시스템이 개발되어야 한다. 이와 같은 관점에서 본 논문에서는 가장 거부감이 없는 생체학적 특징인 얼굴 영상을 이용한 생체 인증 방법에 대해 다루고자 한다. 아울러 현재까지의 생체 측정 방법에 대한 고찰도 행하여 실험에 의한 본 논문의 유용성을 입증하고자 하였다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.257-262
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• 2023

As part of their marketing policy, some suppliers allow retailers a period of credit in anticipation of increasing demand for the products they supply. The opportunity to defer payments on products through credit transactions has the effect of reducing retailers' inventory investment costs, and as a result, retailers determine selling prices in anticipation of increased demand from buyers. This study aims to analyze the inventory model that determines the retailer's selling price and EOQ(Economic Order Quantity) under the assumption that the buyer's demand is an exponentially decreasing function of the retailer's selling price in the credit transaction supply chain consisting of suppliers, retailers, and buyers. The products supplied for problem analysis include the case of deteriorating products that deteriorate over time, and the effect of the credit transaction period, the index of price elasticity and the degree of deterioration on the retailer's selling price and EOQ is analyzed.

• Information Systems Review
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• v.23 no.1
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• pp.69-91
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• 2021

Credit Bureaus in Korea commonly use financial transaction information of the past and present time for calculating an individual's credit scores. Compared to other rating factors, the repayment history information accounts for a larger weights on credit scores. Accordingly, despite full redemption of overdue payments, late payment history is reflected negatively for the assessment of credit scores for certain period of the time. An individual with debt delinquency can be classified into two groups; (1) the individuals who have faithfully paid off theirs overdue debts(Normal Repayment), and (2) those who have not and as differences of creditworthiness between these two groups do exist, it needs to grant relatively higher credit scores to the former individuals with normal repayment. This study is designed to analyze the factors of normal repayment of Korean financial debt delinquents based on credit information of personal loan, overdue payments, redemption from Korea Credit Information Services. As a result of the analysis, the number of overdue and the type of personal loan and delinquency were identified as significant variables affecting normal repayment and among applied methodologies, neural network models suggested the highest classification accuracy. The findings of this study are expected to improve the performance of individual credit scoring model by identifying the factors affecting normal repayment of a financial debt delinquent.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.285-301
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• 2010

Peer-to-peer (P2P) lending is an open marketplace for loans not from bank but from individuals online. Financial transactions are facilitated directly between individuals ("peers") without any intermediation of a traditional financial institution. A market study by renowned research company forecasts that P2P lending will grow very fast and a couple of P2P lending sites in Korea also are getting attentions by providing the alternative financial services. In P2P lending market, Lender will enjoy higher income generated from the loans in the form of interest than interest that can be earned by financial products provided by official financial institutions. Furthermore, lenders are able to decide who they would lend the money for themselves. Meanwhile, borrowers with low credit scores are able to finance their liquidity requirement with low cost and convenient access to the Internet. The objective of this paper is to introduce P2P lending and its issues of information asymmetry. We provide the insights from the case study of one of P2P lending sites in Korea and review the issues in P2P lending market as research topics. Specifically, information asymmetry issues in both traditional financial institutions and P2P lending are discussed.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.25-41
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• 2011

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved them more powerful than traditional artificial neural networks (ANNs) (Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al., 2005; Kim, 2003).The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.818-821
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• 2024

코로나 19(Convid-19) 이후 다가올 미래의 글로벌 신성장산업으로 주목받고 있는 메타버스의 기술이 발전함에 따라 다양한 법적 문제가 떠오르고 있다. 그 중에서도 공연 사용료 징수 문제를 해결하기 위해 본 논문에서는 대용량 처리와 저장, 그리고 유연한 서비스를 제공해줄 수 있는 클라우드와 XGBoost를 활용하여 메타버스 환경에서 사용자에게 공연 사용료의 투명성과 편리성을 제공하는 공연 사용료 징수 시스템을 제안한다.

• Management & Information Systems Review
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• v.35 no.3
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• pp.173-193
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• 2016

The aim of this paper is to extend the TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) to the fuzzy environment for solving the disaster recovery priority decision problem in credit bureau business information system. In this paper, the rating of each information systems and the weight of each criterion are described by linguistic terms which can be expressed in trapezoidal fuzzy numbers. Then, a vertex method is proposed to calculate the distance between two trapezoidal fuzzy numbers. According to the concept of the TOPSIS, a closeness coefficient is defined to determine the ranking order of all information systems. The combination between the fuzzy set and TOPSIS brings several benefits when compared with other approaches, such that the fuzzy TOPSIS require few fuzzy judgements to parameterization, which contributes to the agility of the decision process, it does not limit the number of alternatives simultaneously evaluated, and it does not cause the ranking reversal problem when a new alternative is included in the evaluation process. This paper is demonstrated with a real case study of a credit rating agency involving 9 evaluation criteria and 9 credit bureau business information systems assessed by 6 evaluators, and provide the systematic disaster recovery framework for BCP(Business Continuity Planning) to practitioner. Finally, this paper show that the procedure of the proposed fuzzy TOPSIS method is well suited as a decision-making tool for the disaster recovery priority decision problem in credit bureau business information system.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.191-197
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• 2020

As an effective means of price discrimination, some suppliers offer trade credit to the distributors for the purpose of increasing the demand of the product they produce. The availability of the delay in payments from the supplier enables discount of the distributor's selling price from a wider range of the price option in anticipation of increased customer's demand. In this regard, we consider the problem of determining the distributor's optimal price and lot size simultaneously when the supplier permits delay in payments for an order of a product whose demand rate is represented by a constant price elasticity function. It is assumed that the distributor pays the shipping cost for the order and hence, the distributor's ordering cost consists of a fixed ordering cost and the shipping cost that depend on the order quantity. For the analysis, it is also assumed that inventory is depleted not only by customer's demand but also by decay. We are able to develop a solution algorithm from the properties of the mathematical model. A numerical example is presented to illustrate the algorithm developed.