• 한국수학교육학회지시리즈C:초등수학교육
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• 제26권1호
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• pp.45-63
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• 2023

패턴의 규칙을 찾는 활동은 초등학생들의 대수적 사고를 신장하는 데 유용하다. 본 논문은 초등학생들에게 패턴활동을 지도하는 세 가지 주요 활동, 즉 패턴의 구조를 분석하는 활동, 규칙을 찾아 특정한 항을 구하는 활동, 규칙을 찾아 표현하는 활동을 중심으로 2015 개정 수학과 교육과정에 따른 초등학교 4학년 검정 교과용 도서의 '규칙찾기' 단원에 제시된 패턴 활동의 지도 방안을 분석하였다. 분석 결과 10종 도서에서 증가 수 패턴, 증가 기하 패턴, 계산식 패턴을 중심으로 세 가지 활동이 제시되어 있었다. 패턴의 구조를 분석하는 활동은 대부분 증가 기하패턴을 다룰 때 제시되어 있었는데, 주로 패턴을 이루는 모형의 개수를 구하는 데 초점을 두었다. 반면 규칙을 찾아 특정한 항을 구하는 활동은 세 가지 패턴에서 고루 제시되어 있었고, 대개 가까운 항을 구하는 문항이 많았다. 규칙을 찾아 표현하는 활동은 자신의 언어로 규칙을 이야기해 보거나 써보도록 제시되어 있었다. 이와 같은 분석결과를 토대로 본 연구는 초등학생들의 대수적 사고를 신장하기 위한 패턴 활동의 지도 방안에 대해 교과용 도서의 구성 및 활용 측면에서 구체적인 시사점을 제공한다.

• 정보학연구
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• 제9권3호
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• pp.27-32
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• 2006

If is interested and create rule between it in item that association rules buys, by negative association rules is interested to item that do not buy, it is attempt to do data Maining more effectively. It is difficult that existent methods to find negative association rules find one part of rule, or negative association rules because use more complicated algorithm than algorithm that find association rules. Therefore, this paper presents method to create negative association rules by simpler process using Boolean Analyzer that use dependency between items. And as Boolean Analyzer through an experiment, show that can find negative association rules and more various rule through comparison with other algorithm.

• 산업기술연구
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• 제21권A호
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• pp.147-153
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• 2001

This paper presents techniques for discovering rules with elastic patterns. Elastic patterns are useful for discovering rules from data sequences with different sampling rates. For fast discovery of rules whose heads and bodies are elastic patterns, we construct a suffix tree from succinct forms of data sequences. The suffix tree is a compact representation of rules, and is also used as an index structure for finding rules matched to a target head sequence. When matched rules cannot be found, the concept of rule relaxation is introduced. Using a cluster hierarchy and a relaxation error, we find the least relaxed rules that provide the most specific information on a target head sequence. Performance evaluation through extensive experiments reseals the effectiveness of the proposed approach.

• 산업경영시스템학회지
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• 제23권61호
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• pp.51-58
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• 2000

Discovery of association rules has been used useful in many fields, especially in the fields of the inventory display, catalog design and cross selling. In previous works, all transactions In the database are treated uniformly. In this paper, we present a method for partitioning transactions in the database using time weights. Transactions are assigned different weights as time goes on. Examples show that these method provides purchasing patterns in the database as well as finding association rules.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2003년도 추계공동학술대회
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• pp.621-626
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• 2003

Mining association rules in web log files can be divided into two steps: 1) discovering frequent item sets in web data; 2) extracting association rules from the frequent item sets found in the previous step. This paper suggests an algorithm for finding frequent item sets efficiently The essence of the proposed algorithm is to transform transaction data files into matrix format. Our experimental results show that the suggested algorithm outperforms the Apriori algorithm, which is widely used to discover frequent item sets, in terms of scan frequency and execution time.

• Journal of the Korean Data and Information Science Society
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• 제19권3호
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• pp.925-936
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• 2008

An association rule mining finds the relation among each items in massive volume database. In generating association rules, the researcher specifies the measurements randomly such as support, confidence and lift, and produces the rules. The rule is not produced if it is not suitable to the one any condition which is given value. For example, in case of a little small one than the value which a confidence value is specified but a support and lift's value is very high, this rule is meaningful rule. But association rule mining can not produce the meaningful rules in this case because it is not suitable to a given condition. Consequently, we creat insignificant error which is not selected to the meaningful rules. In this paper, we suggest clustering technique to association rule measures for finding effective association rules using measure of association.

• 산업경영시스템학회지
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• 제21권48호
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• pp.53-63
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• 1998

Mining for association rules between items in a large database of sales transaction has been described as an important data mining problem. The mining of association rules can be mapped into the problem of discovering large itemsets. In this paper we present an efficient algorithm for mining association rules by minimizing the total numbers of candidate 2-itemset, │C$_2$│. More the total numbers of candidate 2-itemset, less the time of executing the algorithm for mining association rules. The total performance of algorithm depends on the time of finding large 2-itemsets. Hence, minimizing the total numbers of candidate 2-itemset is very important. We have performed extensive experiments and compared the performance of our algorithm with the DHP algorithm, the best existing algorithm.

• 한국멀티미디어학회논문지
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• 제7권6호
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• pp.841-850
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• 2004

This paper proposes a GA and GDM-based method for removing unnecessary rules and generating relevant rules from the fuzzy rules corresponding to several fuzzy partitions. The aim of proposed method is to find a minimum set of fuzzy rules that can correctly classify all the training patterns. When the fine fuzzy partition is used with conventional methods, the number of fuzzy rules has been enormous and the performance of fuzzy inference system became low. This paper presents the application of GA as a means of finding optimal solutions over fuzzy partitions. In each rule, the antecedent part is made up the membership functions of a fuzzy set, and the consequent part is made up of a real number. The membership functions and the number of fuzzy inference rules are tuned by means of the GA, while the real numbers in the consequent parts of the rules are tuned by means of the gradient descent method. It is shown that the proposed method has improved than the performance of conventional method in formulating and solving a combinatorial optimization problem that has two objectives: to maximize the number of correctly classified patterns and to minimize the number of fuzzy rules.

• 한국경영과학회지
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• 제6권2호
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• pp.25-34
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• 1981

In this paper, we propose a non-edge following method for linear programs. Unlike alledged poor performance of algorithms of this type, this method performs well at least with 25 randomly generated problems. This method is comparable to Rosen's gradient projection method as applied to the dual formulation. The latter is of general purpose, and no implementation rules are available for linear program applications. This paper suggests ways of finding improving dual feasible directions, and of allowing to move across the extreme faces of a higher dimension polyhedron. Rather simple computational rules are provided for projection operations needed at each iteration.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1998년도 추계학술대회 논문집
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• pp.216-219
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• 1998

This study proposes JPT(Job-Pair Tardiness) that choose operation to be expected to generate better schedule consequence in comparing schedulable operation sets in pair to minimize total tardiness evaluation function in performing scheduling. In result of comparison with existing assignment rules. JPT generates better solution than most other rules in all kinds of problems. So it is anticipated that this is used for initial solution of heuristic and is used for finding more improved solution.