• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.239-253
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• 2024

This research applies both point-wise and pair-wise learning strategies within the learning-to-rank (LTR) framework to predict horse race rankings in Seoul. Specifically, for point-wise learning, we employ a linear model and random forest. In contrast, for pair-wise learning, we utilize tools such as RankNet, and LambdaMART (XGBoost Ranker, LightGBM Ranker, and CatBoost Ranker). Furthermore, to enhance predictions, race records are standardized based on race distance, and we integrate various datasets, including race information, jockey information, horse training records, and trainer information. Our results empirically demonstrate that pair-wise learning approaches that can reflect the order information between items generally outperform point-wise learning approaches. Notably, CatBoost Ranker is the top performer. Through Shapley value analysis, we identified that the important variables for CatBoost Ranker include the performance of a horse, its previous race records, the count of its starting trainings, the total number of starting trainings, and the instances of disease diagnoses for the horse.

• Journal of the Korean Mathematical Society
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• v.46 no.1
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• pp.113-123
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• 2009

A rank one matrix can be factored as $\mathbf{u}^t\mathbf{v}$ for vectors $\mathbf{u}$ and $\mathbf{v}$ of appropriate orders. The perimeter of this rank one matrix is the number of nonzero entries in $\mathbf{u}$ plus the number of nonzero entries in $\mathbf{v}$. A matrix of rank k is the sum of k rank one matrices. The perimeter of a matrix of rank k is the minimum of the sums of perimeters of the rank one matrices. In this article we characterize the linear operators that preserve perimeters of matrices over semirings.

• Journal of Korea Port Economic Association
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• v.27 no.3
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• pp.273-288
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• 2011

Recently, the rankings of Korean container ports in terms of container handling cargo volume were plunged down due to the emerging Chinese ports. The efficient container ports strategies which increase container port competitiveness were requested. In this respect, it is urgently required to draw out constituent factors for Port Logistics, weigh these factors, and finally focus on improving the suggested factors. The aim of this paper is to evaluate weight and priority values for 'inner consisted factors' and 'outer requested factors' of port logistics by using the AHP(Analytic Hierarchy Process) method. As for the analysis regarding the inner consisted factors, the results were shown as follows: a storage and handling system (0.288) as the first rank; an information system of port logistics (0.210) as the second rank; an inland intermodal system (0.189) as the third rank; a ship's entering and departuring system (0.184) as the fourth rank, and a ship's berthing system (0.129) as the fifth rank. In terms of analysis regarding outer requested factors, the results came out as follows: a logistics cost (0.360) as the first rank; a port service (0.128) as the second rank; a connectivity (0.118) as the third rank; a hinterland condition (0.116) as the fourth rank; an convenience (0.106) as the fifth rank; a regional center (0.095) as the sixth rank, and an availability (0.077) as the seventh rank. For analyzing the priorities changes in constituent factors, the comparison of results between the year 2007 and the year 2011 was done. As the results, among inner consisted factors, 'information system of port logistics' was ranked first in the year 2007 while 'a storage and handling system' became the most important factor in the year 2011. Among the inner consisted factors, however, the logistics cost was the important factor in 2007 and 2011, respectively.

• Journal of Korean Academy of Nursing Administration
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• v.9 no.4
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• pp.529-539
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• 2003

Purpose : The objective of this research is to explore the job satisfaction of clinical nurses by the rank of nurse staffing in order to provide effective management for nurses. Method : The research has been conducted on three hundred twenty nurses working at tertiary eight hospitals which were from 2nd rank of nurse staffing to 5th. rank of nurse staffing in Seoul, from August 1 to September 30 of 2003, through survey. For the experimental tools, used Park-Yoon's job satisfaction for nurses(1992) which was modified Stamp's job satisfaction test(1978). The acquired data were analyzed through SPSS program using descriptive method, $x^2$-test, ANCOVA, and LSD. Results : Overall job satisfaction of nurses showed fairly high level of 3.17; in the order of high score, 3.84 for interaction, 3.00 for autonomy, 2.63 for administration. Analysis based of the rank of nurse staffing showed that hospitals of 2nd rank and 3rd. rank of nurse staffing which were higher ratio of patient vs nurse were more satisfied with nurses' job satisfaction than other nurses who were 4th. rank and 5th. rank of nurse staffing. Conclusion : The result of this study revealed that hospital which was higher the rank of nurse staffing was more influenced of nurses' job satisfaction and especially interaction, administration and autonomy which were sub-category of job satisfaction were different among the ranks of nurse staffing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.467-474
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• 2018

To organize and document the contents of meetings and discussions is very important in various tasks. However, in the past, people had to manually organize the contents themselves. In this paper, we describe the development of a system that generates the meeting minutes automatically using the TextRank algorithm. The proposed system records all the utterances of the speaker in real time and calculates the similarity based on the appearance frequency of the sentences. Then, to create the meeting minutes, it extracts important words or phrases through a non-supervised learning algorithm for finding the relation between the sentences in the document data. Especially, we improved the performance by introducing the keyword weighting technique for the TextRank algorithm which reconfigured the PageRank algorithm to fit words and sentences.

• Journal of KIISE
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• v.44 no.2
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• pp.179-185
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• 2017

Document summarization aims to generate a summary that is consistent and contains the highly related sentences in a document. In this study, we implemented for document summarization that extracts highly related sentences from a whole document by considering both similarities and entailment relations between sentences. Accordingly, we proposed a new algorithm, TextRank-NLI, which combines a Recurrent Neural Network based Natural Language Inference model and a Graph-based ranking algorithm used in single document extraction-based summarization task. In order to evaluate the performance of the new algorithm, we conducted experiments using the same datasets as used in TextRank algorithm. The results indicated that TextRank-NLI showed 2.3% improvement in performance, as compared to TextRank.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.101-113
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• 2002

In this paper we introduce a new score generating (unction for the rank regression in the linear regression model. The score function compares the $\gamma$'th and s\`th power of the tail probabilities of the underlying probability distribution. We show that the rank estimate asymptotically converges to a multivariate normal. further we derive the asymptotic Pitman relative efficiencies and the most efficient values of $\gamma$ and s under the symmetric distribution such as uniform, normal, cauchy and double exponential distributions and the asymmetric distribution such as exponential and lognormal distributions respectively.

• Kyungpook Mathematical Journal
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• v.49 no.1
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• pp.183-193
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• 2009

Pseudo-rank functions on Rickart *-rings are introduced and their properties are studied.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.1007-1015
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• 2003

In this paper we introduced a new score generating function for the rank dispersion function in a general linear model. Based on the new score function, we derived the null asymptotic theory of the rank-based hypothesis testing in a linear model. In essence we showed that several rank test statistics, which are primarily focused on our new score generating function and new dispersion function, are mainly distribution free and asymptotically converges to a chi-square distribution.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.745-754
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• 2002

The Google search site (http://www.google.com), which was introduced in 1998, implemented the PageRank algorithm for the first time. PageRank is a ranking method based on the link structure of the Web pages. Even though PageRank has been implemented and being used in various commercial search engines, implementation details did not get documented well, primarily due to business reasons. Implementation techniques introduced in [4,8] are not sufficient to produce PageRank values of Web pages. This paper explains the techniques[4,8], and suggests major data structure and four implementation techniques in order to apply the PageRank algorithm. The paper helps understand the methods of applying PageRank algorithm by means of showing a real system that produces PageRank values of Web pages.