• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.312-319
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• 2002

A recommendation system tracks past action of a group of users to make a recommendation to individual members of the group. The computer-mediated marking and commerce have grown rapidly nowadays so the concerns about various recommendation procedure are increasing. We introduce a recommendation methodology by which Korean department store suggests products and services to their customers. The suggested methodology is based on decision tree, product taxonomy, and association rule mining. Decision tree is to select target customers, who have high purchase possibility of recommended products. Product taxonomy and association rule mining are used to select proper products. The validity of our recommendation methodology is discussed with the analysis of a real Korean department store.

• Journal of Distribution Science
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• v.21 no.4
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• pp.121-129
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• 2023

Purpose: Market basket analysis is one of the most frequently used methods in the retail industry today as a technique to discover the product association. It is empirically analyzed how these product associations differ regionally in the case of the United States. Research design, data, and methodology: Based on the purchasing data of consumer panels collected from 49 US states, the association rules for each state was extracted with the corresponding lift values indicating product association. The difference in lift values in 49 states by the association rule was compared and tested for 49 states and for 4 census regions (Northeast, Midwest, South, West). Results: The association rules of 3/4 of the same association rules show positive associations or negative associations depending on the lift values of the states. There were significant differences in the lift values for 49 states, and for 4 census regions. These significant differences in the lift values were found to be related to the distance between states and whether states belong to the same census region. Conclusions: Retail product associations shown by market basket analysis may vary depending on regional distance or regional heterogeneity. It is necessary to pay attention to these points in multi-store environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.1
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• pp.33-43
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• 2013

The research on data mining that can manage a large amount of information efficiently has grown with the drastic increment of information. Privacy-preserving data mining can protect the privacy of data owners. There are several privacy-preserving association rule, clustering and classification protocols. A privacy-preserving association rule protocol is used to find association rules among data, which is often used for marketing. In this paper, we propose a privacy-preserving k-bits inner product protocol based on Shamir's secret sharing.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.489-498
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• 2007

For better predictions and classifications in customer recommendation, this study proposes an integrative model that efficiently combines the currently-in-use statistical and artificial intelligence models. In particular, by integrating the models such as Association Rule, Frequency Matrix, and Rule Induction, this study suggests an integrative prediction model. The data set for the tests is collected from a convenience store G, which is the number one in its brand in S. Korea. This data set contains sales information on customer transactions from September 1, 2005 to December 7, 2005. About 1,000 transactions are selected for a specific item. Using this data set, it suggests an integrated model predicting whether a customer buys or not buys a specific product for target marketing strategy. The performance of integrated model is compared with that of other models. The results from the experiments show that the performance of integrated model is superior to that of all other models such as Association Rule, Frequency Matrix, and Rule Induction.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.227-230
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• 2003

We can not distinguish semantism of the feature of the current language “big”, “small”, “beautiful”. But we study artificial linguistic interface work and convert natural language to digital binary linguistic theory, we should define the basical conversion process. When we utilize the sum of product fuzzy theory and the visible numerical value, we can establish reasoning rule of input language. Fuzzy theory should be converted to general resulting rule.

• 한국IT서비스학회:학술대회논문집
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• 2003.05a
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• pp.571-576
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• 2003

보험시스템은 상품 및 보험 종류에 따라서 결정되는 요소들이 많고 이에 대한 예외 사항이 많이 존재하는 특성을 가지고 있다. 기존 시스템에서의 상품속성 반영은 테이블을 통한 값 정의와 어플리케이션에서의 예외처리 로직(if then else)을 병행하여 사용함으로 인해, 상품변경과 신상품 개발에 대한 비용이 증가하고 신속한 시장 대응이 어려웠다. 본 논문에서는 보험상품 속성의 비즈니스 로직을 데이터화로 가능하게 하는 Well Formed Rule Base 시스템을 제시하고 실제 프로젝트 적용을 통한 효과를 설명한다.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.2
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• pp.51-61
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• 1991

This paper presents a heuristic method for the Assembly Line Balancing(ALB) of the large-sized product. In the ALB problem of the large-sized product such as bus and truck, the assignments of the Related Task Groups(RTG), the same side tasks, and team tasks should be considered. In this paper, a new concept of the RTG and two kinds of assignment rules are proposed to resolve the above considerations. The first assignment rule allots the RTG with the constraint of the same side tasks to the station while the second allots the RTG to the station, relaxing the above constraint to increase the applicability of the method. An assignment rule for team tasks is also presented. The benefits of the method are to improve work methods, to give more job satisfaction to workers, and to allow greater flexibility in the design of assembly lines.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1361-1364
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• 2012

현대 산업 발전에 따라 대량 생산 체제에서 소비자 개별 주문 요건을 반영하여 생산하는 대량맞춤 생산(Mass Customization) 체제로 변화해가고 있다. 이런 대량맞춤 생산 체제의 제품구성(Product Configuration) 시에 나타나는 CSP(Constraint Satisfaction Problem) 해결 방법론을 제시하고 있다. 기존 방법에서는 복잡 다양한 제약조건을 수학적으로 표현하여 제약 조건 검사에서 소요시간과 검색 공간을 최소화 할 수 있는 알고리즘이 제시했다. 그런데 소비자의 주문 요건들이 빠르게 변화되고 복잡 다양 해지고 있다. 그래서 대상 모델 및 제약조건이 변경이 되었을 경우 기존 방법에서 제시하고 있는 CSP 해결에서는 수정 관리 하기가 쉽지 않고 확장성이 낮다. 본 연구에서는 룰 기반 모델링으로 CSP 문제 해결 프로세스 정립을 하여 관리의 편리성을 제공하고 확장성을 향상시킨다.

• International Commerce and Information Review
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• v.13 no.3
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• pp.143-166
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• 2011

This paper describes the characteristics and outline of rules of origin among Korea and USA, EU, ASEAN. The main focus of this paper is to conduct comparative analysis on rules of origin. Rules of origin are used to determine the country of origin of a product for purposes of international trade. There are two common types of rules of origin depending upon application, the preferential and non-preferential rules of origin Non-preferential rules of origin are used to determine the country of origin for certain purposes. The basis for the non-preferential rules originates from the Kyoto convention which states that if a product is wholly obtained or produced completely within one country the product shall be deemed having origin in that country. For a product which has been produced in more than one country, the product shall be determined to have origin in the country where the last substantial transformation took place. To determine exactly what was the last substantial transformation, three general rules are applied : Change of tariff classification(on any level, though 4-digit level is the most common), Value added-rule.(ad-valorem), and Specific process rule. While criteria of wholly obtained or produced in one country is almost similar to those of theses area and countries, in compliance with value percentages of Substantial Transformation, sufficient working or processing, Korea-US FTA adapts 'Regional Value Content', meanwhile Korea-EU FTA adapts 'Import Content' rule. Finally, Korea-US FTA and ASEAN FTA adapt FOB price for the calculation value added, on the other hand Korea-EU FTA adapts EXW price.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.186-192
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• 1996

A modified learning rule is introduced for the implementation of feedforward artificial neural networks with on-chip learning circuitry using standard analog CMOS technology. Learning rule, is modified form the EBP (error back propagation) rule which is one of the well-known learning rules for the feedforward rtificial neural nets(FANNs). The employed MEBP ( modified EBP) rule is well - suited for the hardware implementation of FANNs with on-chip learning rule. As a ynapse circuit, a four-quadrant vector-product linear multiplier is employed, whose input/output signals are given with voltage units. Two $2{\times}2{\times}1$ FANNs are implemented with the learning circuitry. The implemented FANN circuits have been simulatied with learning test patterns using the PSPICE circuit simulator and their results show correct learning functions.