• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.261-267
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• 2012

In constructing a credit scorecard, each characteristic variable is divided into a few attributes; subsequently, weights are assigned to those attributes in a process called coarse classification. While partitioning a characteristic variable into attributes, one should determine appropriate cutpoints for the partition. In this paper, we propose a cutpoint selection method via penalization. In addition, we compare the performances of the proposed method with classification spline machine (Koo et al., 2009) on both simulated and real credit data.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.194-204
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• 2016

With the fast diffusion of smart media, Webtoon has become popular contents among Korean people. Webtoon's content is being used in various content industries, such as movies and drama, and thus its cultural influence is increasing. Using ordinal Regression analysis, this study tried to find major factors affecting webtoon's success. This study found that readers' rating, number of likes, OSMU, author power, genre, picture style are important factors affecting the success of webtoon. This study has several business implications for the Korean webtoon industry.

• Cartoon and Animation Studies
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• s.16
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• pp.21-32
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• 2009

This study provides an empirical analysis of box office performance for animation movies released in Korea between 2003 and 2008. Two dependent variables are both the number of audiences in the whole country and the number of audiences in Seoul. Such independent variables are employed : power of distributors, the number of screens, release time, sequel/remake, awards, film ratings, nationality, online reviews, and critics' reviews. For the total number of audiences in the whole country, significant variables are the number of screens, the power of USA distributors, Summer release, and online reviews. Since there is no analysis for box office performance for animation movies released in Korean theaters, this study will be considered to be meaningful.

• The Journal of the Korea Contents Association
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• v.18 no.5
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• pp.357-366
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• 2018

This study analyzed the factors affecting box office performance of 200 movies released at the Chinese theater in 2015. The results showed that main actor power, online rating, production power, and Chinese film were sighificant factors which influenced box office, while the distribution power, genre, IP utilization and integration of production and distribution were insignificant. These results mean that online marketing factors such as the popularity index of the main actors evaluated on the internet and the online rating are affecting box office performances in Chinese theaters.

• Journal of KIISE
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• v.44 no.12
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• pp.1333-1337
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• 2017

Recommender systems (RS) that predict a set of items a target user is likely to prefer have been extensively studied in academia and have been aggressively implemented by many companies such as Google, Netflix, eBay, and Amazon. Data imputation alleviates the data sparsity problem occurring in recommender systems by inferring missing ratings and adding them to the original data. In this paper, we point out the drawbacks of existing approaches and make suggestions for data imputation techniques. We also justify our suggestions through extensive experiments.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.4 no.1
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• pp.54-67
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• 1993

This study is to investigate the stress and stress degree in mothers of autistic children. In order to obtain data for planning nursing strategies for mothers of autistic children The assessment tool for the stress was constructed through reviewing literatures on the stress and gathering the stress items by nonstructed face to face interviewing 14 mothers of autistic children The stress tool consists of 74 items each with five point rating scale A data collection was made front 160 mothers of autistic children from 11 institutions for autistic children in Seoul and Kyung-Ki province. The reliability coefficients by Cronbach's a test was 0.94 for the stress scale. The results are as follows : 1) The mean of stress is 3.19, in the area of the etiology, prognosis and the treatment-education, with cause of the treatment the edeucatlon and the prognosis of child's handicap. The mean of stress is 2.85 In the area of the negative of mother's self image, 2.45 in the area of the mother's ordinary life. The mean of stress was 2.05, lowest in the family and social relationship 2) The mean score for the total was 2.62 points. The items with highest stress score were 'All autistic child has not been understood by the society', 'If we die, 1'm afraid that this child will not be cared by someone', 'There is no institution that the child get the schoolibg', etc The stress item with the lowest mean score were 'Keep away the child from husband', 'Being divorced by husband', etc. 3) An analysis of relationship of stress degree to general characteristic shows a statisically significants difference in the number of children in the family and the cognition of the seventy of the child problem

• Journal of Software Engineering Society
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• v.27 no.1
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• pp.8-14
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• 2018

As cloud computing has emerged as a hot trend in the IT industry, various types of cloud services have emerged. In addition, cloud service broker (CSB) technology has emerged to alleviate the complexity of the process of selecting the desired service that user wants among the various cloud services. One of the key features of the CSB is to recommend the best cloud services to users. In general, CSB can use a method to evaluate a service by receiving feedback about a service from users in order to recommend a cloud service. However, since each user has different criteria for giving a rating, there is a problem that reliability of service evaluation can be low when the rating is only used. In this paper, a method is proposed to supplement evaluation of rating based service by applying machine learning based sentiment analysis to cloud service user's review. In addition, the CSB prototype is implemented based on proposed method. Further, the results of comparing the performance of various learning algorithms is proposed that can be used for sentiment analysis through experiments using actual cloud service review as learning data. The proposed service evaluation method complements the disadvantages of the existing rating-based service evaluation and can reflect the service quality in terms of user experience.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1293-1305
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• 2016

In this paper, we develop debt collection predictive models for the person in arrears by utilizing the direct loan data of the Korea Student Aid Foundation. We suggest credit risk scorecards for overdue student direct loan using the developed 3 models. Model 1 is designed for 1 month overdue, Model 2 is designed for 2 months overdue, and Model 3 is designed for overdue over 2 months. Model 1 shows that the major influencing factors for the delinquency are overdue account, due data for payment, balance, household income. Model 2 shows that the major influencing factors for delinquency loan are days in arrears, balance, due date for payment, arrears. Model 3 shows that the major influencing factors for delinquency are the number of overdue in recent 3 months, due data for payment, overdue account, arrears. The debt collection predictive models and credit risk scorecards in this study will be the basis for segmented management service and the call & collection strategies for preventing delinquency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3025-3036
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• 2014

This study was conducted to figure out the influential factors on premenstrual syndrome(PMS) of college female students which are to be utilized as the basic data to develop and apply programs for preventing and controlling such symptom. The subjects were 330 college female students. The data were collected from April 2, 2012 to April 6, 2012. From the results, There has been significant correlation between stress and PMS(r=.36, p<.001) and the attitude to menstruation has appeared to have significant positive correlation with PMS as well(r=.34, p<.001). Multiple regression analysis has been employed to identify the influential factors on PMS and the result has shown that menstrual attitude, grade point average for stress, smoking and dysmenorrhea have been the most significant influential factors with 27% of explanatory power. The level of significance has been high in menstrual attitude(${\beta}$=.28, p<.001), grade point average for stress(${\beta}$=.27, p<.001), smoking(${\beta}$=.20, p<.001) and dysmenorrhea(${\beta}$=.15, p<.001) respectively. In conclusion, it needs to find nursing interventions for PMS related to psychosocial factors and suggest a narrative study for improving quality of life of women with PMS.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.118-129
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• 2022

The purpose of this report is to study a strategic model of promotion activities through various analysis and sales forecasting by selecting wearable products for domestic online companies and collecting sales data. For data analysis, various algorithms are used for analysis and the results are selected as the optimal model. The gradation boosting model, which is selected as the best result, will allow nine independent variables to be entered, including promotion type, price, amount, gender, model, company, grade, sales date, and region, when predicting dependent variables through supervised learning. In this study, the review values set as dependent variables for each type of sales promotion were studied in more detail through the ensemble analysis technique, and the main purpose is to analyze and predict them. The purpose of this study is to study the grades. As a result of the analysis, the evaluation result is 95% of AUC, and F1 is about 93%. In the end, it was confirmed that among the types of sales promotion activities, value-added benefits affected the number of reviews and review grades, and that major variables affected the review and review grades.