• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.32 no.1
• /
• pp.133-150
• /
• 2021

The purpose of this study is to identify the applicability of machine learning targeting titles in the classification of books in public libraries. Data analysis was performed using Python's scikit-learn library through the Jupiter notebook of the Anaconda platform. KoNLPy analyzer and Okt class were used for Hangul morpheme analysis. The units of analysis were 2,000 title fields and KDC classification class numbers (300 and 600) extracted from the KORMARC records of public libraries. As a result of analyzing the data using six machine learning models, it showed a possibility of applying machine learning to book classification. Among the models used, the neural network model has the highest accuracy of title classification. The study suggested the need for improving the accuracy of title classification, the need for research on book titles, tokenization of titles, and stop words.

• Journal of Preventive Medicine and Public Health
• /
• v.54 no.1
• /
• pp.8-16
• /
• 2021

This article aims to introduce the inception and operation of the COVID-19 International Collaborative Research Project, the world's first coronavirus disease 2019 (COVID-19) open data project for research, along with its dataset and research method, and to discuss relevant considerations for collaborative research using nationwide real-world data (RWD). COVID-19 has spread across the world since early 2020, becoming a serious global health threat to life, safety, and social and economic activities. However, insufficient RWD from patients was available to help clinicians efficiently diagnose and treat patients with COVID-19, or to provide necessary information to the government for policy-making. Countries that saw a rapid surge of infections had to focus on leveraging medical professionals to treat patients, and the circumstances made it even more difficult to promptly use COVID-19 RWD. Against this backdrop, the Health Insurance Review and Assessment Service (HIRA) of Korea decided to open its COVID-19 RWD collected through Korea's universal health insurance program, under the title of the COVID-19 International Collaborative Research Project. The dataset, consisting of 476 508 claim statements from 234 427 patients (7590 confirmed cases) and 18 691 318 claim statements of the same patients for the previous 3 years, was established and hosted on HIRA's in-house server. Researchers who applied to participate in the project uploaded analysis code on the platform prepared by HIRA, and HIRA conducted the analysis and provided outcome values. As of November 2020, analyses have been completed for 129 research projects, which have been published or are in the process of being published in prestigious journals.

• Asia-Pacific Journal of Business
• /
• v.11 no.2
• /
• pp.81-98
• /
• 2020

Purpose - This study aims to examine the relationship between Chinese employees' collectivism orientation and organizational commitment and interpersonal helping behavior and verify the differences of such relationships between new and the previous generation of employees. Design/methodology/approach - The 262 Chinese employees participated in self-reported survey through online platform. The confirmatory factor analysis and the hierarchical regression analysis were performed to test hypotheses. Findings - We found that Chinese employees' collectivism orientation positively influenced their organizational commitment and interpersonal helping behavior. Regarding the moderating role of generation, our result revealed that while the positive relationship between collectivism orientation and organizational commitment was significant for previous generation of employees, such relationship was not valid for new generation employees. However, there was no significant generational difference in the relationship between collectivism orientation and interpersonal helping behavior. Research implications or Originality - Considering that there have been relatively few empirical studies examining the interaction between employees' cultural characteristic and generations, this study contributes to demonstrate that the positive influence of Chinese employees' collectivism orientation on organizational commitment vary depending on Chinese generations. In addition, this study provides implications that organizational leaders in China should understand that the generational difference can influence how employees' collectivism orientation leads to their attitudes towards organizations and need to establish human resource management system by reflecting generational difference.

• Journal of the Korea Convergence Society
• /
• v.12 no.3
• /
• pp.125-132
• /
• 2021

This study deals with the influencing factors on flow and addiction perceived by users of Tiktok service, an SFV service platform that is expanding the market in the middle area between social media and OTT. As the number of Tiktok users increases, researchers thought that research on the cause of addiction would be necessary. Since media users lack media consumption time, they produce and share SFVs rather than long videos, and are affected by exogenous variables. In addition, attachment is divided into interpersonal relationships and attachment to services, and the path of attachment was confirmed to be connected to flow and addiction. Through this study, the researchers considered that there were theoretical and practical contributions in that the path leading to addiction of video media services was set and verified as self-exposure and attachment, flow and addiction. These research results can be applied to more diversified video-centered media services, and can be expected to be used for new media emerging in the future.

• The Journal of the Korea Contents Association
• /
• v.20 no.12
• /
• pp.36-48
• /
• 2020

App market has continuously been growth since its launch. The market revenues will reach about 1,000 billion US dollars in 2019. App is a core service for smartphone. Currently, there are more than 1.5 million mobile apps in App platform calling out for attention. So, if you are looking at developing a successful app, you need to have a solid marketing and distribution strategy. Online word of mouth(eWOM) is one of the most effective, powerful App marketing method. eWOM affect potential consumers' decision making, and this effect can spread rapidly through online social network. Despite the increasing research on word of mouth, only few studies have focused on content analysis. Most of studies focused on the causes and acceptance of eWOM and eWOM performance measurement. This study aims to content analysis of mobile apps review In 2013, Google researchers announced Word2Vec. This method has overcome the weakness of previous studies. This is faster and more accurate than traditional methods. This study found out the relationship between mobile app reviews and checked for reactions by Word2vec.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.3
• /
• pp.475-480
• /
• 2021

With the rapid development of mobile, cloud computing technology and social network services, we are in the flood of huge data and realize that these large-scale data contain very precious value and important information. Big data, however, have both latent useful value and critical risks, so, nowadays, a lot of researches and applications for big data has been executed actively in order to extract useful information from big data efficiently and make the most of the potential information effectively. At this moment, the data analysis technique that can extract precious information from big data efficiently is the most important step in big data computing process. In this study, we investigate various data analysis techniques that can extract the most useful information in big data computing process efficiently, compare pros and cons of those techniques, and propose proper data analysis method that can help us to find out the best solution of the big data analysis in the peculiar situation.

• The Journal of Information Systems
• /
• v.31 no.1
• /
• pp.175-195
• /
• 2022

Purpose The purpose of this study is to examine news articles and analyze trends and key agendas related to artificial intelligence(AI). In particular, this study tried to compare the reporting behaviors of Korea and the United States, which is considered to be a leader in the field of AI. Design/methodology/approach This study analyzed news articles using a big data method. Specifically, main agendas of the two countries were derived and compared through the keyword frequency analysis, topic modeling, and language network analysis. Findings As a result of the keyword analysis, the introduction of AI and related services were reported importantly in Korea. In the US, the war of hegemony led by giant IT companies were widely covered in the media. The main topics in Korean media were 'Strategy in the 4th Industrial Revolution Era', 'Building a Digital Platform', 'Cultivating Future human resources', 'Building AI applications', 'Introduction of Chatbot Services', 'Launching AI Speaker', and 'Alphago Match'. The main topics of US media coverage were 'The Bright and Dark Sides of Future Technology', 'The War of Technology Hegemony', 'The Future of Mobility', 'AI and Daily Life', 'Social Media and Fake News', and 'The Emergence of Robots and the Future of Jobs'. The keywords with high centrality in Korea were 'release', 'service', 'base', 'robot', 'era', and 'Baduk or Go'. In the US, they were 'Google', 'Amazon', 'Facebook', 'China', 'Car', and 'Robot'.

• Journal of Korea Entertainment Industry Association
• /
• v.15 no.3
• /
• pp.1-11
• /
• 2021

NC Soft will continue to dream of an entertainment innovation world where customers are connected through game and contents. NC Soft images an expansion in entertainment industry which open doors to the future of enjoy break through innovative online game and creative AI & IT technologies, focused on new business opportunities that are solely NC's own. This study starts with the implication on why focusing on exploration innovation and exploitation strategy at the same time in NC Soft is so challenging. NC Soft manages to their online & mobile gaming competencies in the long term and achieves their sustainable growth by incremental innovation (e.g. game planning, game programming, and graphic design). Also, for innovative success, pursuing exploration strategy is essential. NC Soft have built a strategic alliance spanning K-POP, digital contents platform, movie, and animation, sharing the connectivity of entertainment domains with major contents corporations. The findings of this study would also beneficial to entertainment and contents corporation executives and could provide some road-map on managing the dual challenges of exploration and exploitation implementations.

• International Journal of Internet, Broadcasting and Communication
• /
• v.14 no.1
• /
• pp.85-94
• /
• 2022

Recently, consumers who prefer contactless consumption are increasing due to pandemic trends such as Corona 19. This is the driving force for developing the last mile-based logistics ecosystem centered on the online e-commerce market. Lastmile led to the continued development of the logistics industry, but increased the amount of cargo in urban area, and caused social problems such as overcrowding of logistics. The courier service in the logistics base area utilizes the process of visiting the delivery site directly because the courier must precede the loading work of the cargo in the truck for the delivery of the ordered product. Currently, it's carried out as automated logistics equipment such as conveyor belt in unloading or classification stage, but the automation system isn't applied, so the work efficiency is decreasing and the intensity of the courier worker's labor is increased. In particular, small-scale courier workers belonging to the sub-terminal unload at night at underdeveloped facilities outside the city center. Therefore, the productivity of the work is lowered and the risk of safety accidents is exposed, so robot-based loading technology is needed. In this paper, we have derived the top-level concept and requirements of robot-based loading system to increase the flexibility of logistics processing and to ensure the safety of courier drivers. We defined algorithms and motion concepts to increase the cargo loading efficiency of logistics sub-terminals through the requirements of end effector technology, which is important among concepts. Finally, the control technique was proposed to determine and position the load for design input development of the automatic conveyor system.

• Journal of Appropriate Technology
• /
• v.6 no.2
• /
• pp.211-218
• /
• 2020

Since World Health Organization (WHO) declared Pandemic about COVID-19 at 11 March, 2020, 214 countries now have more than 5.8 million confirmed cases and 360 thousand deaths (29 March 2020). The pandemic of COVID-19 caused lockdown in numerous countries and cities. Strict social distancing also affects most of fields such as health, education, politics, religion, and economy. South Korea actively uses various digital technologies to fight against COVID-19, which is introduced internationally as a successful example. This article introduces the development background and functionalities of COVID-19 Epidemic Investigation Support System (EISS) as well as Smart City Datahub, the core technology that enables the rapid development and application of EISS. Moreover, based on this example, the role and importance of horizontal common platform, such as Datahub, are discussed in the view of future city.