• Information Systems Review
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• v.8 no.2
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• pp.119-138
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• 2006

Association Rule Mining has been successfully used for mining knowledge in static environment but it provides limited features to discovery time-dependent knowledge from multi-point data set. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different multi-point snapshots. This paper proposes a procedure named 'Recursive Change Mining' for detecting continuous change of customer purchase behavior. The Recursive Change Mining Procedure is basically extended association rule mining and it assures to discover continuous and repetitive changes from data sets which collected at multi-periods. A case study on L department store is also provided.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.729-732
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• 2019

데이터로그는 논리형 선언형 프로그래밍 언어로, 특히 재귀적인(recursion) 알고리즘을 표현하기 편리한 언어이다. 대표적인 데이터로그 시스템으로는 CORAL, LogicBlox, XSB, Soufflé가 있다. 본논문에서는 이 네 가지 시스템의 특징을 설명하고, 세 가지 벤치마크, 이행적 폐쇄(Transitive closure), 동세대(same generation), 포인터 분석(pointer analysis)으로 데이터로그 시스템들의 재귀 질의(recursive query) 처리 성능을 비교하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1923-1928
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• 2017

This paper is a study on error correction for three-dimensional shape reconstruction based on factorization method. The existing error correction method based on factorization has a limitation of correction because it is optimized globally. Thus in this paper, we propose our new method which can find and correct the only major error influence factor toward three-dimensional reconstructed shape instead of global approach. We define the error-influenced factor in two-dimensional re-projection deviation space and directly control the error components. In addition, it is possible to improve the error correcting performance by recursively applying the above process. This approach has an advantage under noise because it controls the major error components without depending on any geometric information. The performance evaluation of the proposed algorithm is verified by simulation with synthetic and real image sequence to demonstrate noise robustness.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.51-64
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• 2004

This paper proposes an algerian of generating a tuner-template from multiple fingerprint impressions using a data fusion technique for fingerprint enrollment. The super-template is considered as a single fingerprint template which contains most likely true minutiae based on multiple fingerprint images. The proposed algorithm creates the super template by utilizing a recursive Bayesian estimation method (RBEM), which assumes a sequential fingerprint input model and estimates the credibility of the minutiae in previous input templates froma current input template. Consequently. the RBEM assigns a higher credibility to commonly detectable minutiae from several input templates and a lower credibility to rarely found minutiae from other input templates. Likewise, the RBEM is able to estimate a credibility of the minutia type (ridge ending or bifurcation). Preliminary experiments demonstrate that, as the number of fingerfrint images increases, the performance of recognition can be improved while maintaining the processing time and the size of memory storage for tile super-template almost constant.

• Journal for History of Mathematics
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• v.20 no.4
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• pp.23-48
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• 2007

This study begins from posing a problem, 'formal introduction of mathematical induction in school mathematics'. Most students may learn the mathematical induction at the level of instrumental understanding without meaningful understanding about its meaning and structure. To improve this didactical situation, we research on the historical progress of mathematical induction from implicit use in greek mathematics to formalization by Pascal and Fermat. And we identify various types of thinking included in the developmental process: recursion, regression, analytic thinking, synthetic thinking. In special, we focused on the role of regression in mathematical induction, and then from that role we induce the implications for teaching mathematical induction in school mathematics.

• School Mathematics
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• v.18 no.3
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• pp.625-645
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• 2016

This study clarified the big ideas related to teaching addition and subtraction of fractions with different denominators based on quantitative reasoning with unit and recursive partitioning. An analysis of this study urged us to re-consider the content related to the addition and subtraction of fraction. As such, this study analyzed textbooks and teachers' manuals developed from the fourth national mathematics curriculum to the most recent 2009 curriculum. In addition and subtraction of fractions with different denominators, it must be emphasized the followings: three-levels unit structure, fixed whole unit, necessity of common measure and recursive partitioning. An analysis of this study showed that textbooks and teachers' manuals dealt with the fact of maintaining a fixed whole unit only as being implicit. The textbooks described the reason why we need to create a common denominator in connection with the addition of similar fractions. The textbooks displayed a common denominator numerically rather than using a recursive partitioning method. Given this, it is difficult for students to connect the models and algorithms. Building on these results, this study is expected to suggest specific implications which may be taken into account in developing new instructional materials in process.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.2981-2988
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• 1999

A deductive database consists of facts being the extensional database and rules being the intensional database. Because of the difficulty of evaluating rules, many parallel evaluation algorithms for rules have been presented. But we have not gotten an acceptable result. This paper proposes a new methodology to evaluate proof-theoretic meaning of the linear recursion rule which contains transitive dependency by using a shared-nothing parallel architecture. As first, we prove that there exists the equivalent expression for a linear recursion rule, design the algorithm for evaluating the linear recursion rule based on the equivalent expression, and finally analyse performance of the proposed algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.4
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• pp.41-49
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• 2009

In ubiquitous sensor networks, sensor nodes can be compromised by an adversary since they are deployed in hostile environments. False sensing reports can be injected into the network through these compromised nodes, which may cause not only false alarms but also the depletion of limited energy resource in the network. In the security solutions for the filtering of false reports, the choice of a security threshold value which determines the security level is important. In the existing adaptive solutions, a newly determined threshold value is broadcasted to the whole nodes, so that extra energy resource may be consumed unnecessarily. In this paper, we propose an application of the recursive contract net protocol to determine the threshold value which can provide both energy efficiency and sufficient security level. To manage the network more efficiently, the network is hierarchically grouped, and the contract net protocol is applied to each group. Through the protocol, the threshold value determined by the base station using a fuzzy logic is applied only where the security attack occurs on.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.61-68
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• 2021

Recently, various technologies that use machine learning to classify malicious code have been studied. In order to enhance the effectiveness of machine learning, it is most important to extract properties to identify malicious codes and normal binaries. In this paper, we propose a feature extraction method for use in machine learning using recursive methods. The proposed method selects the final feature using recursive methods for individual features to maximize the performance of machine learning. In detail, we use the method of extracting the best performing features among individual feature at each stage, and then combining the extracted features. We extract features with the proposed method and apply them to machine learning algorithms such as Decision Tree, SVM, Random Forest, and KNN, to validate that machine learning performance improves as the steps continue.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.655-657
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• 1998

합병 문제는 정렬된 두 개의 리스트 A=(a1, a2,....,al)와 B=(b1, b2,....,bm)가 주어질 때, 이두 리스트를 합병하여 하나의 정렬된 리스트 C=(c1, c2,....,cn),n=l+m,로 만드는 문제이다. 지금까지는 {{{{ SQRT {n} }}}}$\times${{{{ SQRT {n} }}}} 메쉬 상에서 odd-even 합병을 재귀적으로 수행하는 O({{{{ SQRT {n} }}}})시간 합병 알고리즘이 주로 사용되었는데, 이 재귀적 합병 알고리즘은 그 기본정책은 간단하나, 메쉬 상에 구현 될때 라우팅과 같은 복잡한 연산이 필요하게 된다. 따라서 본 논문에서는 간단한 행, 열 연산 만을 사용하여 메쉬 상에서 쉽게 구현가능한 O({{{{ SQRT {n} }}}})시 간의 최적 분할 합병 알고리즘을 제안한다.