• Journal of Families and Better Life
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• v.31 no.1
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• pp.99-111
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• 2013

The purpose of this study was to investigate the structural relationships among the related variables of peer relationship. 547 schoolage children's social support, self-esteem, empathy and peer relationship. Subjects of this study were 547 elementary school students residing in Daegu-Si completed questionnaires assessing peer relationship, social support, self-esteem, empathy. The sample variance-covariance matrix was analyzed using AMOS 20.0, and the maximum likelihood minimization function. The goodness of fit was evaluated using the SRMR, RMSEA and its 90% confidence interval, CFI, and TLI. The results were as follow. First, children's social support was found to hadn't direct effect on peer relationship. Second, children's self-esteem, empathy have a direct effect on peer relationship. Third, children's social support have a direct effect on self-esteem, empathy. and children's self-esteem have a direct effect on empathy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.556-563
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• 2017

The purpose of this study is to verify the difference of importance-performance about human right of social worker who works in housing facilities of the disabled. Based on our result, we suggest strategies to implement human rights for the disabled. We collected data from 344 social workers in Busan. We analyzed descriptive statistics, and employed T-Test and Importance-Performance Analysis. Results found the importance level was higher than the performance level of human rights for the disabled. Second, agreement of residential space open and vote right guarantees, the importance level was higher than performance level. Items, excluding ensuring religious activities, prohibiting corporal punishment, strengthening the facility monitoring system and improve facility environment and strengthen program, featured a higher performance level than the importance level. Third, based on the IPA analysis, we derived action strategies for each IPA analysis matrix. We examined 10 items, including free communication included in the first quadrant, improvement of facilities management policy in the second quadrant, prohibition of corporal punishment and strengthening of facility monitoring system in the fourth quadrants.

• Health Policy and Management
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• v.10 no.4
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• pp.99-115
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• 2000

This study was conducted to get a resonable set of budget allocation to public health programs. Matrix Delphi technique was used to obtain the logic of study results and eventually to form a human model which could predict opinion of professionals on budget allocation. Thirty-two professionals in academic and governmental area responded to Delphi survey. Questionnaire was developed using matrix formation, and the matrix was formed by 6 decision criteria on budget allocation and 26 public health programs. The decision criteria are as following: size of problem(morbidity), severity of problem, social equity, importance of prevention, technical feasibility and efficiency of programs. Severity of problem dropped out of the model because it had significant correlation with the size of problem. A total score of each program was obtained by weighting the relative importance of each criteria which also were given by survey respondents. These total scores indicate that the most important public health program is vaccination for infants and children in terms of budget allocation. Monitoring communicable diseases, mental health program, and anti-smoking program are the next. In addition, respondents were asked of the desirable budget size of each program. The result was rearranged by multiple regression model using the scores of each decision criteria. In this process, the current budget size of central government was provided to the respondents, and included in the model. h set of desirable budgets modified using tile model was obtained. Considering the current size of budget, tile results of the model is very different from that of the total score. Managing dementia is ranked the first. Health promotion program for the elderly, rehabilitation of the disabled and monitoring communicable diseases are the next. The need to increase the budget of vaccination for the infants and children was not found as so high. The matrix structure in Delphi survey gave us the precise basis to make optimal decision, and made it possible to develop an opinion predicting model. However the plentifulness and diversity of professional opinions were not fully obtained due to the limited number of decision criteria.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.151-159
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• 2015

This article analyzes English abstracts of the articles published in Journal of the Korean Data & Information Science Society using text mining techniques. At first, term-document matrices are formed by various methods and then visualized by social network analysis. LDA (latent Dirichlet allocation) and CTM (correlated topic model) are also employed in order to extract topics from the abstracts. Performances of the topic models are compared via entropy for several numbers of topics and weighting methods to form term-document matrices.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.49-56
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• 2014

In this paper, we propose a method for identifying hidden principal sentiments among large scale texts from documents, social data, internet and blogs by analyzing standard language, slangs, argots, abbreviations and emoticons in those words. The IRLBA(Implicitly Restarted Lanczos Bidiagonalization Algorithm) is used for principal component analysis with large scale sparse matrix. The proposed system consists of data acquisition, message analysis, sentiment evaluation, sentiment analysis and integration and result visualization modules. The suggested approaches would help to improve the accuracy and expand the application scope of sentiment analysis in social data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.109-134
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• 2018

Collaborative Filtering (CF) is widely used in recommendation field, which can be divided into rating-based CF and learning-to-rank based CF. Although many methods have been proposed based on these two kinds of CF, there still be room for improvement. Firstly, the data sparsity problem still remains a big challenge for CF algorithms. Secondly, the malicious rating given by some illegal users may affect the recommendation accuracy. Existing CF algorithms seldom took both of the two observations into consideration. In this paper, we propose a recommendation method based on listwise learning-to-rank by incorporating users' social information. By taking both ratings and order of items into consideration, the Plackett-Luce model is presented to find more accurate similar users. In order to alleviate the data sparsity problem, the improved matrix factorization model by integrating the influence of similar users is proposed to predict the rating. On the basis of exploring the trust relationship between users according to their social information, a listwise learning-to-rank algorithm is proposed to learn an optimal ranking model, which can output the recommendation list more consistent with the user preference. Comprehensive experiments conducted on two public real-world datasets show that our approach not only achieves high recommendation accuracy in relatively short runtime, but also is able to reduce the impact of malicious ratings.

• Journal of Environmental Impact Assessment
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• v.13 no.4
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• pp.165-185
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• 2004

Assessment in Socio-economic items should be used to estimate social influence when policies and projects were introduced. To estimate current situation of socio-economic items 19 Environmental Impact Statement (EIS) of large scale projects were analyzed. The projects were selected based on magnitude of social impact when the projects were implemented. Environmental Impact Statement was categorized into line projects(road construction, railroad construction, stream development, etc), and surface projects(energy development, wetland reclamation, recreation and sport development, and housing and residential development, etc) thus being chosen for 19 projects in each categories. This report was based on the analysis of 7 items in socio-economic environmental items(i.e., population, residents, industry, public facilities, education, transport and historical monument). Most EIS did not follow the regulation suggested by Ministry of Environment, and only current circumstances were briefly described. Indifference of in-depth analysis of socioeconomic environmental items would influence the process of social and environment impact negatively in the midst of construction of National Projects such as Outer Circle Seoul Highways, Saemankeum Reclamation Projects, etc. This abrupt halt of construction was mostly based on a lack of public hearing or public participation. Socio-economic items are also very much lacking in quantitative method and strengthening socio-economic environmental items is needed via checklist or matrix that brings decision-makers better ideas objectively.

• Journal of Korean Public Health Nursing
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• v.35 no.3
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• pp.415-429
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• 2021

Purpose: The purpose of this study was to explore the health-related factors of the elderly in rural village in-depth and comprehensively based on the socio-ecological model. Methods: The data were collected from 22 elderly people through four focus group interviews and analyzed by deductive content analysis using four themes of the socio-ecological model (SEM) as an analysis matrix. Results: A total of 10 categories corresponding to the four themes of SEM were derived as follows: Intrapersonal level, "Awareness of Aging and Health", "Inefficient practice of health behavior", and "Daunted self-efficacy", Interpersonal level, "Social relations maintenance", and "Changing sense of community", Community level, "Local resources requiring improvement", "Problems caused by regional characteristics", "Disadvantaged group", and "Leadership and residents participation", Public policy level, "Health-related facilities and programs". Conclusion: We proposed the development and application of intervention programs that combined individual activities to improve self-management capacity and group activities to enhance social support and solidarity for rural villagers.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.731-737
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• 2018

The recommendation system is actively researched for the purpose of suggesting information that users may be interested in in many fields such as contents, online commerce, social network, advertisement system, and the like. However, there are many recommendation systems that propose based on past preference data, and it is difficult to provide users with little or no data in the past. Therefore, interest in higher-order data analysis is increasing and Matrix Factorization is attracting attention. In this paper, we study and propose a comparison and replay of the Factorization Machines Leaning(FM) model which is attracting attention in the recommendation system and High-Order Factorization Machines Learning(HOFM) which is a high - dimensional data analysis.

• Journal of Distribution Science
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• v.14 no.9
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• pp.25-29
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• 2016

Purpose - Finding top K persuaders in consumer network is an important problem in marketing. Recently, a new method of computing persuasion scores, interpreted as fixed point or stable distribution for given persuasion probabilities, was proposed. Top K persuaders are chosen according to the computed scores. This research proposed a new definition of persuasion scores relaxing some conditions on the matrix of probabilities, and a method to identify top K persuaders based on the defined scores. Research design, data, and methodology - A new method of computing top K persuaders is computed by singular value decomposition (SVD) of the matrix which represents persuasion probabilities between entities. Results - By testing a randomly generated instance, it turns out that the proposed method is essentially different from the previous study sharing a similar idea. Conclusions - The proposed method is shown to be valid with respect to both theoretical analysis and empirical test. However, this method is limited to the category of persuasion scores relying on the matrix-form of persuasion probabilities. In addition, the strength of the method should be evaluated via additional experiments, e.g., using real instances, different benchmark methods, efficient numerical methods for SVD, and other decomposition methods such as NMF.