• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.107-116
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• 2013

In this paper, we propose a hybrid music recommendation system combining users' listening habits and tag information in a social music site. Most of commercial music recommendation systems recommend music items based on the number of plays and explicit ratings of a song. However, the approach has some difficulties in recommending new items with only a few ratings or recommending items to new users with little information. To resolve the problem, we use tag information which is generated by collaborative tagging. According to the meaning of tags, a weighted value is assigned as the score of a tag of an music item. By combining the score of tags and the number of plays, user profiles are created and collaborative filtering algorithm is executed. For performance evaluation, precision, recall, and F-measure are calculated using the listening habit-based recommendation, the tag score-based recommendation, and the hybrid recommendation, respectively. Our experiments show that the hybrid recommendation system outperforms the other two approaches.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.285-298
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• 2022

Continuous shrinkage priors, as well as spike and slab priors, have been widely employed for Bayesian inference about sparse regression coefficient vectors or covariance matrices. Continuous shrinkage priors provide computational advantages over spike and slab priors since their model space is substantially smaller. This is especially true in high-dimensional settings. However, variable selection based on continuous shrinkage priors is not straightforward because they do not give exactly zero values. Although few variable selection approaches based on continuous shrinkage priors have been proposed, no substantial comparative investigations of their performance have been conducted. In this paper, We compare two variable selection methods: a credible interval method and the sequential 2-means algorithm (Li and Pati, 2017). Various simulation scenarios are used to demonstrate the practical performances of the methods. We conclude the paper by presenting some observations and conjectures based on the simulation findings.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.371-383
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• 2000

Lindsay (1994) and Basu et al (1997) show that another density-based distance called the negative exponential disparity (NED) is an excellent competitor to the Hellinger distance (HD) in generating an asymptotically fully efficient and robust estimator. Bhattacharya and Basu (1996) consider estimation of the locations of several normal populations when an order relation between them is known to be true. They empirically show that the robust HD based weighted likelihood estimators compare favorably with the M-estimators based on Huber's $\psi$ function, the Gastworth estimator, and the trimmed mean estimator. In this paper we investigate the performance of the weighted likelihood estimator based on the NED as a robust alternative relative to that based on the HD. The NED based estimator is found to be quite competitive in the settings considered by Bhattacharya and Basu.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.907-920
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• 2015

Charts based on geometric distribution are effective to monitor the proportion of nonconforming items in high-quality processes where the in-control proportion nonconforming is low. The implementation of this chart is often based on the assumption that in-control proportion nonconforming is known or accurately estimated. However, accurate parameter estimation is very difficult and may require a larger sample size than that available in practice for high-quality process where the proportion of nonconforming items is very small. An inaccurate estimate of the parameter can result in estimated control limits that cause unreliability in the monitoring process. The maximum likelihood estimator (MLE) is often used to estimate in-control proportion nonconforming. In this paper, we recommend a Bayes estimator for the in-control proportion nonconforming to incorporate practitioner knowledge and avoid estimation issues when no nonconforming items are observed in the Phase I sample. The effects of parameter estimation on the geometric chart and the geometric CUSUM chart are considered when the MLE and the Bayes estimator are used. The results show that chart performance with estimated control limits based on the Bayes estimator is generally better than that based on the MLE.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.225-238
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• 2021

The ROC, TOC, and TROC curves, which are visually descriptive methods of exploring the performance of the binary classification model, are implemented with TP, TN, FP, FN which consist of the confusion matrix, as well as their ratios TPR, TNR, FPR, FNR. In this study, we consider two types odds and then propose an odds curve representing these odds. And show the relationship between the odds curve and ROC curve. Based on the odds curve, we propose not only two statistics that measure the discriminant power of the odds curve but also the criteria for validation ratings of the odds curve. According to the shape of the odds curves, two classification distributions can be estimated and a criterion for validation ratings can be determined. The odds curve can be meaningfully used like other visual methods, and two kinds of measures for the discriminant power can be also applied together as an alternative criterion.

• 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.

• Korean Journal of Adult Nursing
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• v.28 no.5
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• pp.546-558
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• 2016

Purpose: This study aimed at the effectiveness to investigate the performance of evidence-based pain assessment and management guidelines. Methods: Participants were 140 nurses at the med-surgical units. Data were collected in early July, 2014 using Registered Nurses Association of Ontario (RNAO) guideline (2007) revised and validated by Hong and Lee (2012) and analyzed by descriptive statistics, t-test, ANOVA using SPSS/WIN18.0. Results: The score of performance of pain assessment guideline was higher than the score of pain management. Categories with high score were pain screening, parameter of pain assessment, documentation, assessment of opioids side-effects, and record of pain caused intervention. Categories with low score were comprehensive pain assessment, multidisciplinary communication, establishing a plan for pain management, consultation and education for patients and their families, and education for nurse. Non-pharmacological management was the lowest one. Conclusion: Assessing and managing pain is a complex phenomenon. It might be useful if institutions host training programs to ensure that nurse are better able to understand and implement pain assessment and management. Since non-pharmacological management is less likely to be used by nurses it may be helpful to include these methods in a training program.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4567-4583
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• 2021

This study proposes an analytical approximation algorithm based on extreme value theory (EVT) for the inverse of the power of the incomplete Gamma function. First, the Gumbel function is used to approximate the power of the incomplete Gamma function, and the corresponding inverse problem is transformed into the inversion of an exponential function. Then, using the tail equivalence theorem, the normalized coefficient of the general Weibull distribution function is employed to replace the normalized coefficient of the random variable following a Gamma distribution, and the approximate closed form solution is obtained. The effects of equation parameters on the algorithm performance are evaluated through simulation analysis under various conditions, and the performance of this algorithm is compared to those of the Newton iterative algorithm and other existing approximate analytical algorithms. The proposed algorithm exhibits good approximation performance under appropriate parameter settings. Finally, the performance of this method is evaluated by calculating the thresholds of space-time block coding and space-frequency block coding pattern recognition in multiple-input and multiple-output orthogonal frequency division multiplexing. The analytical approximation method can be applied to other related situations involving the maximum statistics of independent and identically distributed random variables following Gamma distributions.

• Journal of Home Health Care Nursing
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• v.29 no.2
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• pp.216-224
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• 2022

Purpose: This study aimed to investigate the influence of the perception of the importance of patient safety management and culture on employees' safety performance in small and medium -sized hospitals. Methods: The participants comprised 119 hospital employees, including nurses, doctors, and medical technicians. Data were analyzed through descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients, and multiple regression analysis using the SPSS program. Results: The mean safety performance was 4.09±0.34, mean safety compliance was 4.12±0.44, and safety participation was 4.06±0.38. There were significant differences in safety performance by gender and job. Safety performance and its assocation with both perception of importance on patient safety management and, perception of patient safety culture showed a positive correlation. Safety performance was influenced by the perception of patient safety culture. The explanatory power was 15.7%. Conclusion: Based on these results, improving the perception of patient safety culture is necessary to increase safety performance. To this end developing and applying an interprofessional safety performance education program for employees in small and medium-sized hospitals is vital.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.299-312
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• 2021

Purpose: We provide a condition-based maintenance policy where a surrogate variable is used for monitoring system performance. We constructed a risk function by taking into account the risk and losses accompanied with erroneous decisions. Methods: Assuming a unique degradation process for the performance variable and its specific relationship with the surrogate variable, the maintenance policy is determined. A risk function is developed on the basis of producer's and consumer's risks accompanied with each decision. With a strategic safety factor considered, the optimal threshold value for the surrogate variable is determined based on the risk function. Results: The condition-based maintenance is analyzed from the point of risk. With an assumed safety consideration, the optimal threshold value of the surrogate variable is provided for taking a maintenance action. The optimal solution cannot be obtained in a closed form. An illustrative numerical example and solution is provided with a source code of R program. Conclusion: The study can be applied to situation where a sensor signal is issued if the system performance begins to degrade gradually and reaches eventually its functional failure. The study can be extended to the case where two or more performance variables are connected to a same surrogate variable. Also estimation of the distribution parameters and risk coefficients should be further studied.