• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.148-150
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• 2001

발견된 Web Usage 패턴들은 분석하는 전문가에게는 불필요하고 흥미롭지 못해 의사결정에 도움이 못되는 경우가 많다. 따라서 발견된 패턴에 대한 도메인 전문가의 사전 Belief에 기반한 패턴 검증 과정이 필요하다. 발견된 패턴의 유용성 여부는 패턴의 Unexpectedness를 측정함으로써 결정할 수 있다. 본 논문에서는 패턴의 Unexpectedness를 전문가의 Belief에 기반하여 검증하기 위한 새로운 방법론 제안한다. 발견된 패턴과 전문가 Belief를 매칭 알고리즘을 이용하여 패턴을 4가지(완전일치, 조건부 일치, 결과부 일치, 완전 불일치)로 분류하는 1차 검증과 1차 검증 결과의 4가지 분류데이터를 통계적 추론 방법인 Dempster-chafer에 적용한 2차 검증으로 나뉜다. 1차 검증 과정은 패턴의 분류 용이성을 부여하나 패턴의 Unexpectedness에 대한 신뢰성을 제공하지 못한다. 이 문제점을 2차 검증 과정을 통해 해결한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.913-914
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• 2009

모바일기기의 성능이 점차 발달함에 따라 모바일기기 내에서 로그데이터를 수집한 후 분석하여 사용자의 일상을 요약할 수 있게 되었다. 본 논문에서는 사용자의 GPS 위치정보, 사진 정보들을 모바일기기 내에서 수집하고 사진에 태깅된 사용자의 정보를 바탕으로 의사결정트리 알고리즘을 이용하여 사용자의 하루 일과를 요약한 모바일 사진 블로그를 생성하는 방법을 제안한다. 제안된 시스템으로 모바일기기만 이용하여 사용자의 일상을 효율적으로 요약하여 보여줄 수 있다.

• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.725-735
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• 2008

Due to recent climate change, flood damages have been increased, but it is difficult to construct large hydraulic structure for flood control such as dam because of environmental, economical and political problems. For this reason, several researches and studies have tried to use washland as an alternative of hydraulic facility. Because sizes of washlands are usually smaller than those of dams or reservoirs, there can be many available locations for washlands in a basin and proper combination of these locations can reduce flood disasters efficiently. However, in case there are many available locations for washland and many combinations to consider, it is very difficult to determine the optimal combination which yields to provide the maximum benefit. For the more, hydraulic approach that used in previous studies to calculate flood reduction effect needs a lot of time for calculation and sometimes can not give the final result. In this study, the flood reduction effect of washland is calculated by hydrologic approach and decision making model for optimal location of washland using genetic algorithm for determination of optimal solution is developed. The developed model has been applied to the Ansung River basin in order to examine the applicability and the application result shows that developed model can be used as decision making model for washland.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.89-97
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• 2016

This paper addresses the problem of the construction planning of artillery positions, for which we present an optimization model and propose a heuristic algorithm to solve problems of practical size. The artillery position construction plan includes the assignment of engineers to support the artillery and the schedule of the support team construction sequence. Currently, in the army, managers construct the plan based on their experience. We formulate the problem as a mixed integer program and present a heuristic that utilizes the decomposition of the mixed integer model. We tested the efficacy of the proposed algorithm by conducting computational experiments on both small-size test problems and large-size practical problems. The average optimality gap in the small-size test problem was 6.44% in our experiments. Also, the average computation time to solve the large-size practical problems consisting of more than 200 artillery positions was 79.8 seconds on a personal computer. The result of our computational experiments shows that the proposed approach is a viable option to consider for practical use.

• Journal of Navigation and Port Research
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• v.35 no.8
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• pp.657-665
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• 2011

This study deals with an integrated problem for deciding sequencing and storage location of export containers together at its receiving operation in the container terminal with a perpendicular layout. The preferred storage location of an export container varies with the priority of the corresponding loading operation and the waiting time of an external truck depends on its storage time. This paper proposes the mixed integer programming model considering the expected arrival time and expected finish time of an external truck and the preferred storage location for its loading operation. And we suggest the heuristic algorithm based on a simulated annealing algorithm for real world adaption. We compare the heuristic algorithm with the optimum model in terms of the computation times and total cost and the performance of the heuristic algorithm is analyzed through a numerical experiment.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.30-39
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• 2007

The existing content-based spam mail filtering algorithms have difficulties in filtering spam mails when e-mails contain images but little text. In this thesis we propose an efficient spam mail classification algorithm that utilizes the link structure of e-mails. We compute the number of hyperlinks in an e-mail and the in-link frequencies of the web pages hyperlinked in the e-mail. Using these two features we classify spam mails and legitimate mails based on the decision tree trained for spam mail classification. We also suggest a hybrid system combining three different algorithms by majority voting: the link structure analysis algorithm, a modified link structure analysis algorithm, in which only the host part of the hyperlinked pages of an e-mail is used for link structure analysis, and the content-based method using SVM (support vector machines). The experimental results show that the link structure analysis algorithm slightly outperforms the existing content-based method with the accuracy of 94.8%. Moreover, the hybrid system achieves the accuracy of 97.0%, which is a significant performance improvement over the existing method.

• The Journal of Society for e-Business Studies
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• v.9 no.4
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• pp.19-36
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• 2004

This paper suggests a business process between the collaborative companies that want to extend globally sales and delivery service with restricted physical branches in their own areas. The companies integrate their business processes for sales and delivery services using a shared product taxonomy table. In order to perform the collaborative processes, they need the algorithm to exchange their own products. We suggest a similar product finding algorithm to compose the product taxonomy table that defines product relationships to exchange them between the companies. The main idea of the proposed algorithm is using a multi-attribute decision making (MADM) to find the utility values of products in a same product class of the companies. Based on the values we determine what products are similar. It helps the product manager to register the similar products into a same product sub-category. The companies then allow consumer to shop and purchase the products at their own residence site and deliver them or similar products to another sites.

• Information Systems Review
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• v.22 no.2
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• pp.201-217
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• 2020

Information security is an essential element not only to ensure the operation of the company and trust with customers but also to mitigate uncertain damage by preventing information data breach. Therefore, It is important to select appropriate information security countermeasures and determine the appropriate level of investment. This study presents a decision support model for the appropriate investment amount for each countermeasure as well as an optimal portfolio of information countermeasures within a limited budget. We analyze statistics on the types of information security breach by industry and derive an optimal portfolio of information security countermeasures by using genetic algorithms. The results of this study suggest guidelines for investing in information security countermeasures in various industries and help to support objective information security investment decisions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1055-1060
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• 2018

In the wake of the 4th Industrial Revolution, the problem of career education in schools has become a big issue. While various studies are being conducted on services or technologies to effectively handle artificial intelligence and big data, in the field of education, data on students is simply processed. Therefore, in this paper, we are going to design and present career prediction programs for students using artificial intelligence and big data. Using observational data from students at the institute, the decision tree is constructed with the C4.5 algorithm known to be most intelligent and effective in the decision tree and is used to predict students' path of hope. As a result, the coefficient of kappa exceeded 0.7 and showed a fairly low average error of 0.1 degrees. As shown in this study, a number of studies and data will be deployed to help guide students in their consultation and to provide them with classroom attitudes and directions.

• Korean Journal of Social Welfare
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• v.60 no.1
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• pp.187-209
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• 2008

The authors developed 28 needs assessment tools for integrated assessment centered on needs, which is the core element in care management for the elderly in home. Also, the authors collected the assessment data of 676 elderly persons in home from 120 centers under the Korea Association of Senior Welfare Centers by using the needs assessment tools, and finally developed needs extraction algorithm through decision tree analysis in data mining to identify their actual needs and provide social welfare service suitable for such needs. The needs extraction algorithm for 28 needs of the elderly in home are summarized in