• Information Systems Review
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• v.23 no.1
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• pp.155-172
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• 2021

With the recent increase in online product purchases, a recommender system that recommends products considering users' preferences has still been studied. The recommender system provides personalized product recommendation services to users. Collaborative Filtering (CF) using user ratings on products is one of the most widely used recommendation algorithms. During CF, the item-based method identifies the user's product by using ratings left on the product purchased by the user and obtains the similarity between the purchased product and the unpurchased product. CF takes a lot of time to calculate the similarity between products. In particular, it takes more time when using text-based big data such as review data of Amazon store. This paper suggests a hybrid recommendation system using a 2-phase methodology and text data mining to calculate the similarity between products easily and quickly. To this end, we collected about 980,000 online consumer ratings and review data from the online commerce store, Amazon Kinder Store. As a result of several experiments, it was confirmed that the suggested hybrid recommendation system reflecting the user's rating and review data has resulted in similar recommendation time, but higher accuracy compared to the CF-based benchmark recommender systems. Therefore, the suggested system is expected to increase the user's satisfaction and increase its sales.

• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.489-496
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• 2011

In designing cultural product, end user experiences, feelings and satisfaction with form are one of the most important factors. However, the design processes of cultural product typically depend on traditional methods or intuitive, designer driven methods for generating and evaluating form concepts. We applied sensibility evaluation, analysis method and contemporary digital vehicle design process to cultural product. This paper describes the implementation process of internet based design support system that helps assess user's sensibilities of forms created in each stages of design process. The form focused sensibility evaluation approach provides designers with fast and various feedbacks about their design in each stage. Practical application for exterior design of tourist cart of slowcity(ciitaslow) Shinan was illustrated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1405-1411
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• 2012

This study deals with the case of "Close-to-Nature Improvement Work of Cheonancheon and Wonseongcheon in Cheonan", which has been completed at the end of 2009. The purpose of this study is to evaluate the result of this work and suggest a future direction of development and supplementation of this project. In the course of his study, theoretical researches about urban stream and restoration precedents, observational survey and user questionnaire and comparative analysis have been conducted. According to the study, the most prominent problems of Cheonancheon in comparison with Wonsungcheon are water pollution, low use and participation of residents. As location based future development concept, Cheonancheon as various event space for visitors, Wonsungcheon as recreational space for residents are suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2665-2673
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• 2015

The purpose of this study is to develop a web-based database system to manage effectively data collected to evaluate program learning outcomes (PO) in a nursing school. The database management system (DBMS) was developed using a software development life cycle method: Analysis, Design, Implementation, and Evaluation. The demands for the content and system of users were collected. The system structure, database using an entity-relationship modeling, and user interface were designed based on the demands. The designed DBMS was created using GWT, Java and Apache HTTP server. The expert group and users evaluated the implemented DBMS. Problems derived from them were modified. The average of end-user computing satisfaction evaluated by 8 nursing faculty and 5 teaching assistants was 4.14 (SD =.44). The web-based PO DBMS makes it possible for nursing faculty members to access and use much of the information needed for analysis and decision-making.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.195-216
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• 2022

In this study, the author applied the service design methodology to the university library to maximize the service value provided by the university library. To this end, the 'Double Diamond Model', a service design model, was applied to the university library, and service design tools such as Persona, Customer Journey Map, and Touch Points were utilized. To reflect on the service design in the university library, the author first reviewed the literature related to the subject and researched the previous studies. Then, the issue was discovered by questionnaire surveys, interviews with users and librarians, and field investigations. Based on this, Persona and situation scenarios were derived. In addition, after synthesizing Persona's situational behavior and user's emotional change, the study visualized the Customer Journey Map and suggested service improvement plans for 11 items in 3 areas. This study is focused on the process of deriving service improvement plans rather than improving a specific service. The purpose of this study was to improve university library service and to suggest new service plans. The significance of this study is that the practical service improvement plans were applied to the university library.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.2
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• pp.119-135
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• 2014

This study is aimed at understanding the factors behind deciding to accept a social network service (SNS) from the viewpoint of tourists who are users of tourism SNS. The study also seeks to clarify the effects these deduced factors have on the intention of users to continuously use SNS. To this end, individual properties (such as self-efficacy, socio-cultural effects, social presence and people's innovativeness), systematic properties (like system quality and information quality)and usefulness/availability were used as factors with regard to the decision to accept tourism SNS based on previous studies and efforts were made to structurally clarify the effects of such previous factors on people's intention to continuously use SNS through perceived value and satisfaction. SNS had significant effects on satisfaction and, furthermore, significantly affected tourists' intention to continuously use it. Based on such study results, factors behind deciding to accept SNS from the viewpoint of tourists affected customers' perceived value and satisfaction and ultimately affected their intention to continuously use SNS. To achieve the purpose of the study, a survey was conducted on about 250 Busan residents who had used SNS in relation to tourist activities, such as exhibitions, conventions, accommodation, trips, aviation service and transportation. According to an empirical study, factors behind deciding to accept tourism SNS, including individual properties, systematic properties and usefulness/availability had statistically significant effects on perceived value. The usefulness/availability factor had the largest influence, in particular, followed by the systematic factor and individual factor. The value perceived in the process of using tourism SNS had significant effects on satisfaction and, furthermore, significantly affected tourists' intention to continuously use it. Based on such study results, factors behind deciding to accept SNS from the viewpoint of tourists affected customers' perceived value and satisfaction and ultimately affected their intention to continuously use SNS.

• Journal of vocational education research
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• v.37 no.4
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• pp.45-66
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• 2018

The purpose of this study is to explore the factors affecting the social capital of youth and to draw implications for the policies related to development of the social capital of them. To this end, we utilized the OLS regression model and the quantile regression model exploiting the 12th year dataset of the Korean Education & Employment Panel(KEEP). First, this study shows that the effect on trust is higher than that of the counterpart when the case is a) unmarried, b) with the high level of education, c) with a large asset, d) with high self-respect and the satisfaction for financial situation, and e) social media user. On the other hand, the higher the monthly average income, the lower the trust level. In addition, when the cases are grouped into 25 quantile, 50 quantile, and 75 quantile according to the level of trust, it is revealed empirically that the factors affecting social capital formation are somewhat different. Second, this study also shows that the effect is higher in a specific condition. The effect is higher compared to the counterpart when the case is a) male, b) with children, c) metropolitan city resident, d) non-employee, e) with a large asset, f) with high level of happiness, g) with high expense of purchasing books, and h) social media user. As a result, it is found that there are no personal characteristics that have statistically significant influence on students belonging to the 25th quantile of social capital. This study suggests that, in order to support the formation of social capital of Korean youths, it is necessary to enhance their psychological satisfaction and to provide cultural support or policies. In addition, it suggests that a tailored social capital accumulation program is needed according to the level of social capital, and the support for this need to be changed according to the amount of social capital of young people.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.63-83
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• 2021

The appearance of education is also rapidly changing in social changes represented by social networks. And the development of information and communication technology is also having a widespread effect on the education field. In the era of untact caused by Covid-19, education through smart learning is having a greater effect on students as well as adult learners more quickly and broadly. In addition, smart learning is not just limited to learning content, but is developing into personalized, convergence, and intelligent. The purpose of this study is to identify the factors of ARCS motivation theory that can determine the learning motivation of smart learning users, and to empirically study the casual relationship between these factors on education achievement through practical value and hedonic value. Specifically, I would like to examine how the independent variables ARCS motivation factors (attention, relevance, confidence, and satisfaction) affect learners' education achievement through the parameters of practical value and hedonic value. To this end, a research model was presented that applied the main variables of attention, relevance, confidence, and satisfaction, which are four elements of ARCS motivation theory, a specific and systematic motivational strategy to induce and maintain learners' motivation. In order to empirically verify the research model of this study, a survey was carried out on learners with experience using smart learning. As a result of the study, first attention was found to have a positive effect on the hedonic value. Second, relevance was found to have a positive effect on the hedonic value. Third, it was found that confidence did not have a positive effect on the practical value and the hedonic value. Forth, satisfaction was found to have a positive effect on the practical value and the hedonic value. Fifth, practical value was found to have a positive effect on the education achievement. Sixth, hedonic value was found to have a positive effect on the education achievement. Through this, it can be seen that the intrinsic motivation of learners using smart learning affects the education achievement of users through intrinsic and extrinsic value. A variety of smart learning that combines advanced IT technologies such as AI and big data can contribute to improving learners' education achievement more effectively and efficiently. Furthermore, it can contribute a lot to social development.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.30 no.1
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• pp.121-143
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• 2019

The purpose of this study was to examine the reason and value system of the elderly people on the public library use in Korea. For the purpose, a questionnaire survey was conducted for elderly aged over 60, from 15 public libraries in Seoul from October 29 to October 10, 2018, and 306 valid responses collected were analyzed. The value system is based on the Means-end Chain (MEC) Theory, and the linkage between the attributes, consequences, and values of public library use is figured out as a value hierarchy. As a result, the most frequently revealed value system was 'reads or borrows books (attribute) ${\rightarrow}$ gets new knowledge (consequence) ${\rightarrow}$ satisfies oneself (value).' For the value reached by using the public library, both groups answered that their satisfaction, achievement, fun, pleasure, and vitality. However, the elderly aged 65 and over additionally felt that public libraries are good for their mental / physical health. The results showed that the elderly people using the public library feels the traditional functions of the public library as the main attribute, and the public library could provide the elderly people with contribution to the lively old age.