• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.209-212
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• 2013

The Nuri process of emphasis by the Ministry of Education to promote is standardized curriculum at the national level for the education and care. It is to improve the quality of pre-school education and Ensure a fair starting line early in life and It emphasizes character education in all areas of the window. Nuri the process of development of a the insect robot for the Creativity education Increased the interesting and educational effects. Assembly and the effect on learning of educational content using a VR educational robot using the existing floor assembly using the online website to help assemble and learning raised. Order to take advantage of information technology in the information-based society requires the active interest and motivation in learning, creative learning toddlers learning robot are also needed. A three-dimensional model of the robot, and augmented by linking through the marker, the target marker and the camera relative to the coordinate system of augmented reality, seeking to convert the marker to be used in augmented reality marker patterns within a pre-defined patternto be able to make a decision on what of. The fusion of a smart education through training and reinforcement the educational assembly of the robot in the real world window that is represented by a virtual environment in this paper to present a new form of state-of-the-art smart training, you will want to lay the foundation of the nation through the early national talent nurturing talent.

• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.541-549
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• 2015

Research about U.S. and European countries demonstrated that startups and young firms account for nearly all net job creation. If we want to bring down unemployment and to increase economic growth rate, we need to create new companies and to make them to grow. Credit availability is one of the most important factors for entrepreneurs as they attempt to start or expand a business. For young firms, access to credit for business growth can mean the difference between survival and failure. Equity crowdfunding is an innovative means of raising capital for businesses. Crowdfunding campaigns can give new business access to a large pool of investors. This brings huge benefits for marketing and increase provability of success of business and ROI, so it leads follow-on investment from Venture Capital and Angel investors. In Korea, the survival rate of startups and average growth rate of survivors is far lower than those of the U.S or other countries due to lack of funds for startup or early business growth. Equity crowdfunding can be a new funding source for venture or startups. It can increase startup and survival rate, in addition to the growth rate of survivors, resulting in decreased unemployment rate. In Korea, Equity crowdfunding will be available from 2016. Further study is needed to determine whether the impact of crowdfunding in Korea on job creation will be similar to its impact in the U.S.

• Journal of the Korean Society for Library and Information Science
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• v.31 no.1
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• pp.7-28
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• 1997

To investigate the present states and analyze the need of continuing education, a survey was done to the library and information professionals. Based on the personal membership file of the Korean Library Association, 292 members were selected using $25\%$ systematic sampling method. Questionnaires were mailed to them and $80\%$ returned. Of the total respondents. $90\%$ want to participate continuing education, however only $50\%$have a formal continuing education experience during last 3 years. Informal educational efforts are also weak and show much individual differences. $67\%$ of the libraries encourage continuing education but only $25\%$ of the respondents were provided with time and money for participation. The most favored mode of the continuing education Is one week course specialized In particular topic$(31.1\%)$ or area$(25.5\%)$. New methods, such as CD-ROM. online etc. were also preferred. Respondents regard professional association, society, and the library Information science department of university as desirable leading organization for continuing education. Among the 16 possible topics to be educated, respondents showed substantially higher Interest(more than $50\%$) In 5topics, and there were significant need differences In 7 topics among groups divided by library type.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.486-500
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• 2015

This study focuses on customer loyalty that explains how firms can maintain long-term relationship with customers, in the internet shopping and mobile shopping contexts. Specifically, this study examines the key determinants of customer loyalty from two perspectives: service quality and shopping value. Concerning service quality, previous studies have long argued that it is a starting point of building customer loyalty. Shopping value is a key variable in capturing consumers' shopping motives. In this study, we consider two types of shopping value: usefulness as utilitarian value and enjoyment as hedonic value. Moreover, this study examines whether the effects of service quality and shopping value on customer loyalty differ depending on internet and mobile shopping groups. To test the proposed hypotheses, we conducted multiple linear regression analysis and chow test with a total of 199 data collected on users who have experience in internet shopping and mobile shopping. The key findings are as follows: First, in the internet shopping group, customer loyalty depends on service quality (responsiveness and empathy) and usefulness, whereas in the mobile shopping, it only depends on enjoyment. Second, the impacts of service quality and shopping value on customer loyalty are different depending on internet shopping and mobile shopping. The results imply that e-tailors should develop differential methods suitable for internet shopping or mobile shopping to enhance customer loyalty.

• Journal of Science and Technology Studies
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• v.20 no.1
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• pp.39-85
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• 2020

With the development of information technology, fake news is becoming a serious social problem. Individual measures to manage the problem, such as fact-checking by the media, legal regulation, or technical solutions, have not been successful. The flood of fake news has undermined not only trust in the media but also the general credibility of social institutions, and is even threatening the foundations of democracy. This is why one cannot leave fake news unchecked, though it is certainly a difficult task to accomplish. The problem of fake news is not about simply judging its veracity, as no news is completely fake or unquestionably real and there is much uncertainty. Therefore, managing fake news does not mean removing them completely. Nor can the problem be left to individuals' capacity for rational judgment. Recurring fake news can easily disrupt individual decision making, which raises the need for socio-technical measures and multidisciplinary collaboration. In this study, we introduce a new public online platform for fake news management, which incorporates a multidimensional and multidisciplinary approach based on citizen science. Our proposed platform will fundamentally redesign the existing process for collecting and analyzing fake news and engaging with user reactions. People in various fields would be able to participate in and contribute to this platform by mobilizing their own expertise and capability.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.329-338
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• 2014

Today, one of the important factors that determine the university rating is the employment rate. The jobseekers are using online or offline recruiting services in order to get the desired job information. There are lots of employment supporting systems as like web-based employment agencies and University's job centers, but they are focusing more on providing job information rather than on managing the employment support. In addition, those are insufficient to support business process associated with MOU companies, industry field training, mentoring processors, etc., and to continue to manage and to update the information (resume, personal statement, etc.) about the students which the companies want, and the information about the companies which jobseekers want. Therefore, it is required that the employment supporting system which not only storages the initial data (student and corporate information), but also assist the career placement. In this paper, we considered the specific employment rights management features of the existing employment support system, it could receive real-time job information in the smart phone, we presented the design and construction of the system linked to the Bachelor Information System.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.159-170
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• 2016

In this study, the authors examine the ways in which social media ultimately affects the attachment of individuals to their favorite brands. Through an analysis of data using multiple linear regression, this study finds that SNS (social networking site) users that post status updates for a wide audience have no bearing on the individual's use of socialization agents. Those who consume social news passively are, however, likely to depend on socialization agents for determining their final purchase decisions. Socialization agents, both personal and non-personal, also play a role in the formation of brand attachment among individuals who depend on these social sources. Based on these results, marketers are encouraged to establish an online footprint of a social nature to formulate brand awareness and to provide a means for users of social media to improve their brand attachments to their favored brands. As this research was conducted exclusively in the predominantly collective culture of South Korea, further studies could attempt to analyze social networking use and socialization agent use via a cross-culture study, particularly one including an individualistic culture.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.125-137
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• 2011

Product reviews in online shopping sites can serve as a useful guideline to buying decisions of customers. However, due to the massive amount of such reviews, it is almost impossible for users to read all the product reviews. For this reason, e-commerce sites provide users with useful reviews or statistics of ratings on products that are manually chosen or calculated. Opinion mining or sentiment analysis is a study on automating above process that involves firstly analyzing users' reviews on a product to tell if a review contains positive or negative feedback, and secondly, providing a summarized report of users' opinions. Previous researches focus on either providing polarity of a user's opinion or summarizing user's opinion on a feature of a product that result in relatively low usage of information that a user review contains. Actual user reviews contains not only mere assessment of a product, but also dissatisfaction and flaws of a product that a user experiences. There are increasing needs for effective analysis on such criteria to help users on their decision-making process. This paper proposes a model that stores various types of user reviews in a data warehouse, and analyzes integrated reviews dynamically. Also, we analyze reviews of an online application shopping site with the proposed model.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.535-542
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• 2013

Since case-based reasoning(CBR) has many advantages, it has been used for supporting decision making in various areas including medical checkup, production planning, customer classification, and so on. However, there are several factors to be set by heuristics when designing effective CBR systems. Among these factors, this study addresses the issue of selecting appropriate neighbors in case retrieval step. As the criterion for selecting appropriate neighbors, conventional studies have used the preset number of neighbors to combine(i.e. k of k-nearest neighbor), or the relative portion of the maximum similarity. However, this study proposes to use the absolute similarity threshold varying from 0 to 1, as the criterion for selecting appropriate neighbors to combine. In this case, too small similarity threshold value may make the model rarely produce the solution. To avoid this, we propose to adopt the coverage, which implies the ratio of the cases in which solutions are produced over the total number of the training cases, and to set it as the constraint when optimizing the similarity threshold. To validate the usefulness of the proposed model, we applied it to a real-world target marketing case of an online shopping mall in Korea. As a result, we found that the proposed model might significantly improve the performance of CBR.

• The Journal of Bigdata
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• v.5 no.1
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• pp.11-27
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• 2020

In this paper, we developed a big data platform to store, process, and analyze effectively on such education longitudinal study data. And it was applied to the Seoul Education Longitudinal Study(SELS) to confirm its usefulness. The developed platform consists of data preprocessing unit and data analysis unit. The data preprocessing unit 1) masking, 2) converts each item into a factor 3) normalizes / creates dummy variables 4) data derivation, and 5) data warehousing. The data analysis unit consists of OLAP and data mining(DM). In the multidimensional analysis, OLAP is performed after selecting a measure and designing a schema. The DM process involves variable selection, research model selection, data modification, parameter tuning, model training, model evaluation, and interpretation of the results. The data warehouse created through the preprocessing process on this platform can be shared by various researchers, and the continuous accumulation of data sets makes further analysis easier for subsequent researchers. In addition, policy-makers can access the SELS data warehouse directly and analyze it online through multi-dimensional analysis, enabling scientific decision making. To prove the usefulness of the developed platform, SELS data was built on the platform and OLAP and DM were performed by selecting the mathematics academic achievement as a measure, and various factors affecting the measurements were analyzed using DM techniques. This enabled us to quickly and effectively derive implications for data-based education policies.