• Journal of Korean Society for Quality Management
• /
• v.46 no.3
• /
• pp.539-550
• /
• 2018

Purpose: The purpose of this study was to find meaningful patient groups of disease using foreign patients data and analyze implemented test of the patient groups. Methods: The data was collected by foreign patients' EMR data of K university hospital. The author proposed tree-form patients' characteristic diagram through statistical methods that association rule, proportion test, clustering using prescription information and questionnaire information. Results: This study's analysis process was applied high blood data and diabetes data. Analysis showed other characteristic of meaningful patient groups in high blood and diabetes. In high blood, test implementation rate of patient group showed the differences. And in diabetes, test implementation rate of patient group and implemented test list showed differences. Conclusion: The result of this study can play a role as basic data that can be clinical testing standard in preventive aspect. Eventually, 5 dimensions of SERVQUAL will be improved by this study's process.

• Journal of the Korea Convergence Society
• /
• v.11 no.11
• /
• pp.19-24
• /
• 2020

Recently, due to the rapid increase of pets, there is a need for an integrated pet-related personalized product recommendation service such as feed recommendation using a health status check of pets and various collected data. This paper implements a product recommendation system that can perform various personalized services such as collection, pre-processing, analysis, and management of pet-related data using big data. First, the sensor information worn by pets, customer purchase patterns, and SNS information are collected and stored in a database, and a platform capable of customized personalized recommendation services such as feed production and pet health management is implemented using statistical analysis. The platform can provide information to customers by outputting similarity product information about the product to be analyzed and information, and finally outputting the result of recommendation analysis.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.14 no.4
• /
• pp.35-45
• /
• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.5
• /
• pp.171-177
• /
• 2019

In this paper, we analyze the current phenomenon of child abuse crimes based on the information gathered by the National Child Protection Agency. The purpose of this paper is to diagnose the seriousness of child abuse by biological parents based on the analyzed information and propose measures against it. Comprehensive and integrated measures are needed for child abuse committed by biological parents due to abuse concealment, continuity of damage, and inactive national intervention by considering punishment on attackers through national intervention, fundamental in-depth psychological counseling, therapeutic care, promoting recovery of victims, and ultimately continuous and regular management and monitoring as a long-terms measure. To do so, developing customized and individual educational programs and make them obligations can be first presented to identify child abuse in advance and build up preventive systems based on the principle of family preservation. In addition, problems should be addressed at a fundamental level by performing various and active therapeutic treatments such as psychological treatment, mental treatment, or drug treatment gradually and through phases for biological parents who commit child abuse and contributing to recovering the relationship. Furthermore, proper protection and treatment service should be provided to children victimized by abuse by extending professional children care facilities and adopting the professional family commission system as measures by separating family.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.1
• /
• pp.143-152
• /
• 2023

In the rapidly changing information age, as the need for Informatization education increases, it is necessary to further activate Informatization education for adults. First, in terms of lifelong learning, this researcher suggested learner analysis, class subject materialization, and lecture environment confirmation as three things to be considered first before the course is opened. And as a matter to be continuously considered in terms of lifelong learning, this researcher considered that the connection with the next quarter class and the continuity of learning opportunities should be considered. This study attempted to reveal the differentiated characteristics of informatization education in terms of lifelong education by presenting and analyzing three actual class cases taught by this researcher at lifelong education institutions. Its characteristics included customized education in the information age, continuous upgrades of equipment, instructor education in response to the information age, and expansion of employment opportunities. Based on the case of information education classes, this study, which analyzed the differentiated characteristics of information education at the lifelong education level, can help improve the quality of instructors and self-development of learners in the actual educational environment. For this, continuous follow-up research will also be needed.

• Proceedings of the KSR Conference
• /
• 2008.06a
• /
• pp.913-918
• /
• 2008

When developing railway vehicle system, investigation of the dynamical stability is essential as a virtual prototyping process. Not only the verification using the commercial analysis tools, systematic analysis using customized tools is also necessary, because these can give other points of view in stability, which is sometimes unable to evaluate in the former one. As a solver platform for customization, it is important to derive basic theory about flexible bodies and build flexible structure, which enables easy module insertion of user-created functions. In the paper, a flexible dynamic analysis system is developed, using absolute cartesian coordinate, modal coordinate and absolute nodal coordinate. Each coordinate system is verified by respective examples for every system. This solver system will play an important role for building the basic platform for analysis system, keeping pace with the concurrent development of the modules, such as wheel-contact force, constraints and user-defined force modules. Using the information from the analysis, the evaluation of the dynamic behavior of the train and its stability analysis will be available.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.179-196
• /
• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.7 no.1
• /
• pp.75-84
• /
• 2011

The e-learning contents offered in the current educational system does not appropriately reflect the needs of actual users in the planning and development phases. Considering this problem, this study sets the following four topics as its research: Stability of e-learning; Obstacles of the applications of e-learning; e-learning contents that users wants to be offered besides lectures; and methods of e-learning, and based on these goals, it aims at determining the 'needs of the users for the promotion of e-learning. As the target of the study, a survey was conducted with 200 students who have experienced taking e-learning classes in four universities located in Eastern Seoul, which have introduced an e-learning system. The data collected from the survey went through data coding and data cleaning processes and were analyzed by year, major, and department using SAS 9 statistics package program. The result of this study showed that developing and offering services of e-learning contents that are customized to students based on their majors and year can become an effective plan for promoting e-learning.

• Journal of the Korean Home Economics Association
• /
• v.42 no.3
• /
• pp.195-209
• /
• 2004

The purpose of this study was 1) to examine the usage of mobile internet by cell phone or palm pilot, etc., 2) to analyze mobile users' lifestyles, 3) to examine preferred fashion services according to users' lifestyles and 4) to investigate service satisfaction and preference with the mobile internet. 193 university students in Seoul were randomly selected as subject. The data was analyzed using descriptive statistics (i.e., percentage, frequency), factor analysis, cluster analysis and ANOVA. The results of the study were as follows: first, most mobile users spent 10 min a day for using the mobile internet (i.e., short message service) mainly in transportation vehicles. Secondly, five factors in the mobile users' lifestyle were named as: 'surfer', 'absorber', 'expert', 'accepter' and 'enthusiast'. Thirdly, two factors in the preferences of fashion service on mobile internet were 'customized information service' and 'ordinary information service'. Fourthly, according to the internet lifestyle, mobile users were classified into three groups: 'mania group', 'follower group', and 'veteran group'. The mania group was the highest group in mobile service satisfaction and service preference. Marketing implications are discussed for the successful mobile business in clothing and textile industry.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.5
• /
• pp.139-147
• /
• 2019

This study is conducted to analyze how Social Media characteristics of restaurant franchise affect customer decision making and redelivery intention and find out how to do Social Media marketing which is getting important. Through this study, we will understand the direction of Social Media management. In this study, we had 220 users to respond questionnaires who looked up about restaurant franchise through Social Media. In the previous research, we classified the Social Media characteristics about the restaurant franchise into the fields of liveliness, agreement, reliability, communication, accuracy, and entertainment. In order to verify the hypothesis, we conducted single regression analysis and multiple regression analysis and verified the relationship between variables. First, we found that Social Media characteristics of restaurant franchise has a positive relationship with favorability. Second, Social Media characteristics of restaurant franchise has a positive relationship with satisfaction. Third, favorability has a positive effect on satisfaction. Fourth, favorability has a positive effect on the intention of re-inquiry and redeliver. Fifth, satisfaction has a positive effect on the revisit and intention to redirect. As a result of the study, we found that restaurant franchise will gain trust of customers if they take into account the characteristics of Social Media of restaurant franchise and conduct customized marketing according to the head office of restaurant franchise and perform continuous feedback and management in order to improve customer's favorability and loyalty.