• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.45-54
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• 2008

As mobile Web technology becomes more increasingly applicable. the mobile contents market. especially the music downloading for mobile phones, has recorded remarkable growth. In spite of this rapid growth, customers experience high levels of frustration in the process of searching for desired music contents. It affects to a re-purchasing rate of customers and also. music mubile content providers experience a decrease in the benefit. Therefore, in aspects of a customer relationship management (CRM), a new way to increase a benefit by providing a convenient shopping environment to mobile customers is necessary. As an solution for this situation, we propose a new music recommender system to enhance the customers' search efficiency by combining collaborative filtering with mobile web mining and ordinal scale based customer preferences. Some experiments are also performed to verify that our proposed system is more effective than the current recommender systems in the mobile Web.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.85-94
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• 2013

As the financial market becomes larger, the loss increases due to the failure of the credit risk managements from the poor management of the customer information or poor decision-making. Thus, the credit risk management also becomes more important and it is essential to develop a credit scoring model, which is a fundamental tool used to minimize the credit risk. Credit scoring models have been studied and developed only for binary target variables. In this paper, we consider other types of target variables such as ordinal multinomial data or longitudinal binary data and suggest credit scoring models. We then apply our developed models to real data and random data, and investigate their performance through Kolmogorov-Smirnov statistic.

• Journal of Korean Academy of Nursing
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• v.51 no.1
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• pp.5-14
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• 2021

Purpose: This study aimed to investigate sub-health status (SHS) of people living in China during the Coronavirus disease 2019 (COVID-19) COVID-19 pandemic. COVID-19 is a severe acute respiratory syndrome coronavirus (SARS-CoV) infection-induced acute infectious disease, which is featured by universal susceptibility and strong infectivity, and SHS (a status of low quality health) refers to a status of low-quality health. COVID-19 has gradually developed into a global pandemic, making the public in a high stress situation in physiological, psychological and social states in the short term. Methods: From March 6 to 11, 2020, a large-scale cross-sectional survey was conducted by convenient sampling, and SHS assessment scale was used in the questionnaire. The ordinal logistic regression analysis was used to identify the factors affecting SHS. Results: In this study, 17,078 questionnaires were delivered with 16,820 effective questionnaires collected, and 10,715 subjects (63.7%) were found with SHS, with moderate SHS primarily. Physiological sub-scale scored the highest, followed by psychological and social sub-scales. Ordinal logistic regression analysis indicated that man, only-child, workers and farmers were risk factors of SHS. Protective factors of SHS included living in rural areas and townships, laid-off retirees and education degree. Conclusion: It shows many people in China place in a poor health status during COVID-19 pandemic. It is necessary that relevant departments pay more attention to people with poor health such as men, only-child, urban people, workers and farmers, and groups with high education degree during and after pandemic stabilization.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.591-597
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• 2022

As social anxiety is increasing due to the spread of the COVID-19 epidemic, the responses at the level of local governments are also changing depending on the characteristics. We analyzed the factors influencing perceptions of social safety as they relate to the trustworthiness of local governments. Based on a 2020 social survey of 16 cities, counties, and districts in Busan Metropolitan City, the effects of householder characteristics, economic characteristics, local attachment characteristics, and social safety perception characteristics on the reliability of the local government were analyzed through an ordinal logistic regression analysis. It was found that the more vulnerable the class was and the safer the region was, the higher the trust was in the basic local government. In order to respond and preemptively recover damage in natural and social disaster situations, continuous efforts are needed to strengthen the capabilities of basic local governments.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1648-1652
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• 2004

An advanced training machine designed for elderly people is proposed. The training machine allows users to have a safe and effective training through exercise close to ordinal motion appears in daily life such as standing up/down motion. The activation level of user's muscle is real timely monitored during the exercise and the training load is adjusted based on the body information. The training load is exerted and continuously controlled by actuation of an air cylinder.

• IE interfaces
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• v.15 no.2
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• pp.209-217
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• 2002

Quality of Service(QoS) in the telecommunications can be evaluated by analyzing the opinion data which result from the surveyed opinions of respondents and quantify subjective satisfaction on the QoS from the customers' viewpoints. For analyzing the opinion data, MOS(mean opinion score) method and Cumulative Probability Curve method are often used. The methods are based on the scoring method, and therefore, have the intrinsic deficiency due to the assignment of arbitrary scores. In this paper, we propose an analysis method of the opinion data using logit models which can be used to analyze the ordinal categorical data without assigning arbitrary scores to customers' opinion, and develop an analysis procedure considering the usage of procedures provided by SAS(Statistical Analysis System) statistical package. By the proposed method, we can estimate the relationship between customer satisfaction and network performance parameters, and provide guidelines for network planning. In addition, the proposed method is compared with Cumulative Probability Curve method with respect to prediction errors.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.358-363
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• 1998

An algorithm for representing the cubic spline interpolation of differentiable functions by a fuzzy system is presented in this paper. The cubic B-spline functions which form a basis for the interpolation function are used as the fuzzy sets for input fuzzification. The ordinal number of the coefficient cKL in the list of the coefficient cij's as sorted in increasing order, is taken to be the output fuzzy set number in the (k, l) th entry of the fuzzy rule table. Spike functions are used for the output fuzzy sets, with cij's as support boundaries after they are sorted. An algorithm to compute the support boundaries explicitly without solving the matrix equation involved is included, along with a few properties of the fuzzy rule matrix for the designed fuzzy system.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.151-161
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• 1997

An easy Monte Carlo Gibbs sampling approach is suggested for Bayesian analysis of cumulative logit models for ordinal polytomous data. Because in the cumulative logit model the posterior conditional distributions of parameters are not given in convenient forms for random sample generation, appropriate latent variables are introduced into the model so that in the new model all the conditional distributions are given in very convenient forms for implementation of the Gibbs sampler.

• Journal of the Korea Safety Management & Science
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• v.9 no.3
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• pp.165-171
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• 2007

Dependent models in quality statistics are classified as serially autocorrelated model, multivariate model and dependent sample model. Dependent sample model is most efficient in time and cost to obtain samples among the above models. This paper proposes to implement parametric and nonparametric models into production system depended on demand pattern. Nonparametric models have distribution free and asymptotic distribution free techniques. Quality statistical models are classified into two categories ; the number of dependent sample and the type of data. The type of data consists of nominal, ordinal, interval and ratio data. The number of dependent sample divides into 2 samples and more than 3 samples.

• Communications for Statistical Applications and Methods
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• v.21 no.4
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• pp.275-284
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• 2014

Matched pairs are twice continuously measured data with the same categories. They can be represented as the square contingency tables. We can also consider symmetry and marginal homogeneity. Moreover, we can infer the matched pairs models; the symmetry model, the quasi-symmetry model, and the ordinal quasi-symmetry model. These inferences are involved in assumptions for special distributions. In this study, we visualize matched pairs models using modified correspondence analysis. Modified correspondence analysis can be used when square contingency tables are given; consequently, it is involved in the square and asymmetric correspondence matrix. This technique does not need assumptions for special distributions and is more helpful than the correspondence analysis to visualize matched pairs models.