• Journal of the Korean Mathematical Society
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• v.31 no.4
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• pp.645-657
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• 1994

If S is a semiring of nonnegative reals, which linear operators T on the space of $m \times n$ matrices over S preserve the column rank of each matrix\ulcorner Evidently if P and Q are invertible matrices whose inverses have entries in S, then $T : X \longrightarrow PXQ$ is a column rank preserving, linear operator. Beasley and Song obtained some characterizations of column rank preserving linear operators on the space of $m \times n$ matrices over $Z_+$, the semiring of nonnegative integers in [1] and over the binary Boolean algebra in [7] and [8]. In [4], Beasley, Gregory and Pullman obtained characterizations of semiring rank-1 matrices and semiring rank preserving operators over certain semirings of the nonnegative reals. We considers over certain semirings of the nonnegative reals. We consider some results in [4] in view of a certain column rank instead of semiring rank.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.169-179
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• 1998

Median rank is used to systemize the evaluation of research personnel in a research institution. Suggested evaluation system is purposed to enhance the fairness, distinguish the factors of evaluation and maximize the synergy of researchers. The factors of evaluation are largely divided into the subjective and the objective factor. The final rank of the researchers is determined with the converted median rank value. The propriety of applying median rank is tested by Spearman's rank correlation coefficient. We also suggest the method of determining the rank of researchers. This evaluation system is not fixed in special case but can be changed in situation. It also can be applied to any other personnel evaluation system through the appropriate revision.

• Journal of Korea Port Economic Association
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• v.25 no.2
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• pp.95-114
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• 2009

The aim of this paper is to evaluate weight and priority values for 'inner consisted factors' and 'outer requested factors' of logistics system using the AHP(Analytic Hierarchicy Process) method. As for analysis regarding inner consisted factors, the results were shown as follows: a road transportation (0.312) as first rank; a marine transportation (0.269) as second rank; a railway transportation (0.239) as third rank; an air transportation (0.118) as fourth rank, and a pipeline transportation (0.063) as fifth rank. In terms of analysis regarding outer requested factors, the results were came out as follows: an infrastructure (0.322) as first rank; a performance (0.206) as second rank; an information system (0.151) as third rank; a human resources (0.121) as fourth rank, a business environment (0.075) as fifth rank; a connectivity (0.073) as sixth rank, and a political environment (0.052) as seventh rank.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.803-811
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• 2010

This study analyzes the characteristics of preference ratings by dividing estimated values into four groups according to rank correlation coefficient after obtaining preference estimated value to user's ratings by using collaborative filtering algorithm. It is known that the value of standard error of skewness and standard error of kurtosis lower in the group of higher rank correlation coefficient This explains that the preference of higher rank correlation coefficient has lower extreme values and the differences of preference rating values. In addition, top n recommendation lists are made after obtaining rank fitting by using the result ranks of prediction value and the ranks of real rated values, and this top n is applied to the four groups. The value of top n recommendation is calculated higher in the group of higher rank correlation coefficient, and the recommendation accuracy in the group of higher rank correlation coefficient is higher than that in the group of lower rank correlation coefficient Thus, when using standard error of skewness and standard error of kurtosis in recommender system, rank correlation coefficient can be higher, and so the accuracy of recommendation prediction can be increased.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.5
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• pp.14-28
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• 2009

The PageRank algorithm is an important component for ranking Web pages in Google and other search engines. While many improvements for the original PageRank algorithm have been proposed, it is unclear which variations (and their combinations) provide the "best" ranked results. In this paper, we evaluate the ranking quality of the well-known variations of the original PageRank algorithm and their combinations. In order to do this, we first classify the variations into link-based approaches, which exploit the link structure of the Web, and knowledge-based approaches, which exploit the semantics of the Web. We then propose algorithms that combine the ranking algorithms in these two approaches and implement both the variations and their combinations. For our evaluation, we perform extensive experiments using a real data set of one million Web pages. Through the experiments, we find the algorithms that provide the best ranked results from either the variations or their combinations.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.18-33
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• 2014

A Word is the smallest unit for text analysis, and the premise behind most text-mining algorithms is that the words in given documents can be perfectly recognized. However, the newly coined words, spelling and spacing errors, and domain adaptation problems make it difficult to recognize words correctly. To make matters worse, obtaining a sufficient amount of training data that can be used in any situation is not only unrealistic but also inefficient. Therefore, an automatical word extraction method which does not require a training process is desperately needed. WordRank, the most widely used unsupervised word extraction algorithm for Chinese and Japanese, shows a poor word extraction performance in Korean due to different language structures. In this paper, we first discuss why WordRank has a poor performance in Korean, and propose a customized WordRank algorithm for Korean, named KR-WordRank, by considering its linguistic characteristics and by improving the robustness to noise in text documents. Experiment results show that the performance of KR-WordRank is significantly better than that of the original WordRank in Korean. In addition, it is found that not only can our proposed algorithm extract proper words but also identify candidate keywords for an effective document summarization.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.110-114
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• 2010

We describe a new method for text categorization using TextRank algorithm. Text categorization is a problem that over one pre-defined categories are assigned to a text document. TextRank algorithm is a graph-based ranking algorithm. If we consider that each word is a vertex, and co-occurrence of two adjacent words is a edge, we can get a graph from a document. After that, we find important words using TextRank algorithm from the graph and make feature which are pairs of words which are each important word and a word adjacent to the important word. We use classifiers: SVM, Na$\ddot{i}$ve Bayesian classifier, Maximum Entropy Model, and k-NN classifier. We use non-cross-posted version of 20 Newsgroups data set. In consequence, we had an improved performance in whole classifiers, and the result tells that is a possibility of TextRank algorithm in text categorization.

• Journal of the Korean Mathematical Society
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• v.52 no.3
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• pp.625-636
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• 2015

The Boolean rank of a nonzero $m{\times}n$ Boolean matrix A is the least integer k such that there are an $m{\times}k$ Boolean matrix B and a $k{\times}n$ Boolean matrix C with A = BC. We investigate the structure of linear transformations T : $\mathbb{M}_{m,n}{\rightarrow}\mathbb{M}_{p,q}$ which preserve Boolean rank. We also show that if a linear transformation preserves the set of Boolean rank 1 matrices and the set of Boolean rank k matrices for any k, $2{\leq}k{\leq}$ min{m, n} (or if T strongly preserves the set of Boolean rank 1 matrices), then T preserves all Boolean ranks.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.385-387
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• 2012

Succinct 표현은 n개의 이산 객체를 정수 값으로 표현하는 대신 이진화하여 표현하는 방법으로 o(n) bit만을 사용하는 공간 효율적인 방법이다. Succinct 표현을 위한 1차원 비트스트링은 이산 객체의 저장 위치에 접근하기 위해서 rank와 select 함수를 필요로 하며, 다양한 연구들에 의해 현재 rank와 select 함수는 o(n) 비트를 사용하여 O(1) 시간에 수행되고, 실용적인 구현이 가능하다. 또한, 2차원 비트 스트링에 대한 연구도 진행되어, 현재 O($n^2$) bit를 사용하여 O(logn) 시간에 rank를, O($log^2n$) 시간에 select를 수행할 수 있다. 본 논문에서는 2차원 비트스트링 상에서의 rank 및 select 함수를 새롭게 정의하고 o($n^2$) 비트만을 사용하여 O(logn) 시간에 rank 질의를, 그리고 O($log^2n$)시간에 select 질의를 수행할 수 있는 방법을 제안한다.

• Asia pacific journal of information systems
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• v.25 no.3
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• pp.548-562
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• 2015

The growing popularity of mobile application has led to researchers and practitioners needing to understand users' mobile application download behaviors. Using large-scale transaction data obtained from a leading Korean telecommunications company, we empirically explore how application download rank, which appears to users when they decide to download a new application, affects their extended mobile application download. This terminology refers to downloading an additional application in the same category as those that they have already downloaded. We also consider IT characteristics, user characteristics, and application type that might be associated with the extended application download. The analysis generates the following result. Overall, a higher rank of a new application encourages the extended application download, but the linear relationship between the rank and the extended application download disappears when critical rank points are incorporated into the model. Further, no quadratic effect of rank is found in the extended application download. Based on the results, we suggest theoretical and managerial implications.