• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.

• Journal of Korean Home Economics Education Association
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• v.19 no.4
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• pp.37-56
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• 2007

The purpose of this study is to provide basic resources to the first-grade Home Economics Regular Teacher Qualification Program (FGHERTQP) in order to improve its operation plans. For the study, the three methods were carried out: an analysis on the curricula of FGHERTQP over six years since 2000, a questionnaire asking their satisfaction degrees and needs on the programs which was answered by the home economics teachers who were the participants of FGHERTQP, and several statistical analyses such as a descriptive-test, a $X^2$-test, a t-test, and one way ANOVA by using SPSS Win ver 10.0. The results of the study were as follows; Firstly, FGHERTQP has been operated ten times by five training centers during resent six years. Subject matters ($1{\sim}7$), whole numbers of lectures ($11{\sim}29$), and their allotted working hours ($111{\sim}136$) vary with individual training centers and operation years. Secondly, when using 5 point likert scales, Contents and Methods of evaluation marked 3.08 which were the lowest scores, and Qualification Training in General marked 3.72 which was the highest score among five fields of Qualification Training in General, Contents, Organizations, Methods and Evaluation. The overall scores were low. Thirdly, in needs analysis on offering subject matters, the participants wanted to study the field of home economics education more than that of subject contents. Looking about the highest needs classified by domains, Food Principles & Meal Management showed the highest in Foods. And Consumer Issues in Clothing & Textiles in Textiles, Upcoming Housing Cultures in Housing, Family Relationship in Child Development & Family Relationship, Juveniles and their daily life as a consumer in Family & Consumer Resources Management. Fourthly, training centers' lectures available had a significant influence on the satisfaction degrees according to general characteristic variations of the participants. That is, as a training center offers more lectures in the field of subject education than those of subject contents, the participants showed higher satisfaction degrees (p<.05).

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Journal of Nutrition and Health
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• v.42 no.1
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• pp.23-37
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• 2009

The purpose of this study was to investigate the health status of preschool children using the questionnaires about dietary behaviors and anthropometric indices. And also nutritional status was investigated using questionnaires for 24-hr recall method. The study was conducted in 145 children aged 3 to 6 years and questionnaires for dietary behaviors and dietary intakes were performed by mothers of children in Ulsan. Just nine percent of children were graded as good in terms of having healthy eating habits, this means that the nutrition education for the dietary behaviors should be more focused on preschool children. With regard to the frequency of food intake, children consumed green & yellow vegetables less frequently, meanwhile consumed high protein source food (meat, egg and bean) and milk and its product more frequently. Children almost never consumed fried foods as often as 1-2 times a weak. In assessment of the health status, children have the highest prevalence of colds and allergy, but lower prevalence of clinical symptoms due to the nutritional deficiency. The mean height was $103.6\;{\pm}\;6.4\;cm$ and significantly different among age (p < 0.05), but was not significantly different between sex. The mean weight was $17.8\;{\pm}\;3.0\;kg$ and significantly different in 5, 6years old among age. By the WLI criteria, 11.1% of children were underweight and 17.4% of children were overweight or obese. By the Rohrer index criteria, any children were not underweight and 86.8% of children were overweight or obese. By the Kaup index criteria, 2.8% of children were underweight and 29.2% of children were overweight or obese. And Obesity Index criteria, 2.1% of children were underweight and 20.8% of children were overweight or obese. The results of obesity rate by all criteria except Rohrer index indicated similar level, were significantly high in age 3 with all criteria, and decreased with age increased. The energy intake of children was lower than EER (Estimated Energy Requirements) of Dietary Reference Intakes for Koreans (KDRIs) by as much as 85.7%. Acceptable Macronutrient Distribution Ranges (AMDR) was 62.6:21.5:15.7 as carbohydrate:protein:lipid, so children consumed protein more, but consumed lipid less compared with those of KDRIs. Vitamin A intake was 133% of recommended intakes (RI) and calcium intake which was identified as the nutrient most likely to be lacking in diets was 98.9% of RI. The intakes of all minerals and vitamins except folate were higher than KDRIs. 33.3% of children were distributed in insufficiency of energy intake, 42.7% of children were distributed in insufficiency of lipid intake. These results indicate that the need of developing of nutrition education program and further concern of a public health center, university and children care center about dietary life for preschool children.