• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.930-937
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• 2001

For ranking fuzzy numbers, comparisons between numbers are necessary However, the comparison results can be vague since fuzzy numbers represent vague numeric values. Thus, ranking results of fuzzy numbers which are based on comparisons between fuzzy numbers, could also be vague. This means that there could be several possible ranking sequences of fuzzy numbers. There have been proposed many ranking methods for fuzzy numbers. However, most of them generate only ranking sequence. In this paper, we present a ranking method for fuzzy numbers using the fuzzy satisfaction function, Our method generates several possible ranking sequences of the given fuzzy numbers using the fuzzy satisfaction function.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.709-717
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• 2010

The task of association rule mining is to find certain association relationships among a set of data items in a database. There are three primary measures for association rule, support and confidence and lift. In this paper we developed a association rule ranking function using conditional probability increment ratio. We compared our function with several association rule ranking functions by some numerical examples. As the result, we knew that our decision function was better than the existing functions. The reasons were that the proposed function of the reference value is not affected by a particular association threshold, and our function had a value between -1 and 1 regardless of the range for three association thresholds. And we knew that the ranking function using conditional probability increment ratio was very well reflected in the difference between association rule measures and the minimum association rule thresholds, respectively.

• Journal of Information Science Theory and Practice
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• v.1 no.3
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• pp.6-11
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• 2013

A new explanation, using exponential functions, is given for the S-shaped functional relation between the mean citation score and the proportion of top 10% (and other percentages) publications for the 500 Leiden Ranking universities. With this new model we again obtain an explanation for the concave or convex relation between the proportion of top $100{\theta}%$ publications, for different fractions of ${\theta}$.

• Journal of applied mathematics & informatics
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• v.29 no.1_2
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• pp.337-349
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• 2011

This paper is concerned with deriving necessary and sufficient optimality conditions for a fuzzy linear programming problem. Toward this end, an equivalence between fuzzy and crisp linear programming problems is established by means of a specific ranking function. Under this setting, a main theorem gives optimality conditions which do not seem to be in conflict with the so-called Karush-Kuhn-Tucker conditions for a crisp linear programming problem.

• The KIPS Transactions:PartD
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• v.18D no.2
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• pp.101-110
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• 2011

According to the increasing use of blogs, a huge number of posts have appeared in a blogosphere. This causes web surfers to face difficulty in finding the quality posts in their search results. As a result, post ranking algorithms are required to help web serfers to effectively search for quality posts. Although there have been various algorithms proposed for web-page ranking, they are not directly applicable to post ranking since posts have their unique features different from those of web pages. In this paper, we propose post ranking algorithms that exploit actions performed by bloggers. We also evaluate the effectiveness of post ranking algorithms by performing extensive experiments using real-world blog data.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.145-148
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• 2002

Type-1 fuzzy value is used to show the uncertainty in a given value. But there exist many situations that it needs to be extended to type-2 fuzzy value because it is difficult to determine the crisp membership function itself. Intrinsically type-2 fuzzy values are more expressive and powerful than type-1 fuzzy values, but, at the same time, more difficult to be compared or ranked . In this paper, a ranking method for type-2 fuzzy values is proposed. It is based on the satisfaction function which shows the possibility that one type-2 fuzzy value is greater than the other type-2 fuzzy value Some properties of the proposed method are also analyzed .

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.333-341
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• 2004

In the real world there are many linear programming problems where all decision parameters are fuzzy numbers. Several approaches exist which use different ranking functions for solving these problems. Unfortunately when there exist alternative optimal solutions, usually with different fuzzy value of the objective function for these solutions, these methods can not specify a clear approach for choosing a solution. In this paper we propose a method to remove the above shortcoming in solving fuzzy number linear programming problems using the concept of expectation and variance as ranking functions

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.1005-1012
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• 2009

The area under the curve(AUC) is commonly used as a measure of the receiver operating characteristic(ROC) curve which displays the performance of a set of binary classifiers for all feasible ratios of the costs associated with true positive rate(TPR) and false positive rate(FPR). In the bipartite ranking problem where one has to compare two different observations and decide which one is "better", the AUC measures the quantity that ranking score of a randomly chosen sample in one class is larger than that of a randomly chosen sample in the other class and hence, the function which maximizes an AUC of bipartite ranking problem is different to the function which maximizes (minimizes) accuracy (misclassification error rate) of binary classification problem. In this paper, we develop a way to construct the unified framework for AUC maximizer including support vector machines based on maximizing large margin and logistic regression based on estimating posterior probability. Moreover, we develop an efficient algorithm for the proposed unified framework. Numerical results show that the propose unified framework can treat various methodologies successfully.

• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.397-405
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• 2010

Data mining is the method to find useful information for large amounts of data in database, and one of the important goals is to search and decide the association for several variables. The task of association rule mining is to find certain association relationships among a set of data items in a database. There are three primary measures for association rule, support and confidence and lift. In this paper we developed a association rule ranking function by decreased lift influence to generate association rule for items satisfying at least one of three criteria. We compared our function with the functions suggested by Park (2010), and Wu et al. (2004) using some numerical examples. As the result, we knew that our decision function was better than the function of Park's and Wu's functions because our function had a value between -1 and 1regardless of the range for three association thresholds. Our function had the value of 1 if all of three association measures were greater than their thresholds and had the value of -1 if all of three measures were smaller than the thresholds.

• Journal of the Korean Institute of Landscape Architecture
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• v.33 no.4 s.111
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• pp.97-107
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• 2005

This study was carried out to construct accurate and scientific system of assessment indicators in selection of National Trust conservation areas, which was new concept of domestic environment movement and offer the raw data of new analytic method by introducing the fuzzy theory and weight for overcoming the uncertainty of ranking decision. To transform the Likert's scale granted to assessment indicators into the type of triangular fuzzy number(a, b, c), there was conversion to each minimum(a), median(b), and maximum(c) in applying membership function, and in using the center of gravity and eigenvalue, there was to decide the ranking. The rankings of converted values applied a mean importance and weight were confirmed that they were generally changed. Therefore, the ranking decision was better to accomplish objective and rational ranking decision by applying weight that was calculated in grouping of indicator than to judge the singular concept and to be useful in assessment of diverse National Trust site. In the future, because AHP, which was general method of calculating weight, was lacked, there was to understand the critical point to fix a pertinent weight, and to carry out the study applying engineering concept like fuzzy integral using $\lambda-measure$.