• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.301-311
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• 2020

With the recent global urban issues such as climate change, urbanization, and energy problems, the smart city was proposed as one of the solutions in urban planning. This study introduces the smart city initiatives of South Korea by examining the recent history of smart city policies and their limitations. This case study reflects the experience of one of the countries which thrived to building smart cities as their national key industries to drive economic growth. It also analyzes the trends of the smart city using big data analysis techniques. Although there are obstacles such as economic recession, failing to differentiate from the U-city, low service level than expected smart functionality, We could recognize the current status of the smart city policies in South Korea such as 1) Korean smart city development projects are actively implemented, 2) public consensus suggests that applying advanced technology and the active role of government need, 3) a comprehensive and strategic approach with the integration and application of advanced technologies is required as well, 4) investment by both private and public sectors need to deliver social improvements. This study suggests future direction of smart city polity in South Korea in the conclusion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.1085-1089
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• 2015

Text-mining technique in the past had difficulty in realizing the analysis algorithm due to text complexity and degree of freedom that variables in the text have. Although the algorithm demanded lots of effort to get meaningful result, mechanical text analysis took more time than human text analysis. However, along with the development of hardware and analysis algorithm, big data technology has appeared. Thanks to big data technology, all the previously mentioned problems have been solved while analysis through text-mining is recognized to be valuable as well. However, applying text-mining to Korean text is still at the initial stage due to the linguistic domain characteristics that the Korean language has. If not only the data searching but also the analysis through text-mining is possible, saving the cost of human and material resources required for text analysis will lead efficient resource utilization in numerous public work fields. Thus, in this paper, we compare and evaluate the public document classification by handwork to public document classification where word frequency(TF-IDF) in a text-mining-based text and Cosine similarity between each document have been utilized in big data environment.

• Journal of People, Plants, and Environment
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• v.22 no.5
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• pp.455-466
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• 2019

This study was carried out to analyze trends in floral products and services through the big data analysis of various social networking services (SNSs) and then to provide objective marketing directions for the floricultural industry. To analyze the big data of SNSs, we used four analytical methods: Cotton Trend (Social Matrix), Naver Big Data Lab, Instagram Big Data Analysis, and YouTube Big Data Analysis. The results of the big data analysis showed that SNS users paid positive attention to flower one-day classes that can satisfy their needs for direct experiences. Consumers of floral products and services had their favorite designs in mind and purchased floral products very actively. The demand for flower items such as bouquets, wreaths, flower baskets, large bouquets, orchids, flower boxes, wedding bouquets, and potted plants was very high, and cut flowers such as roses, tulips, and freesia were most popular as of June 1, 2019. By gender of consumers, females (68%) purchased more flower products through SNSs than males (32%). Consumers preferred mobile devices (90%) for online access compared to personal computers (PCs; 10%) and frequently searched flower-related words from February to May for the past three years from 2016 to 2018. In the aspect of design, they preferred natural style to formal style. In conclusion, future marketing activities in the floricultural industry need to be focused on social networks based on the results of big data analysis of popular SNSs. Florists need to provide consumers with the floricultural products and services that meet the trends and to blend them with their own sensitivity. It is also needed to select SNS media suitable for each gender and age group and to apply effective marketing methods to each target.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.3
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• pp.347-370
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• 2022

Most public library websites provide unstructured cultural program data, which cannot be produced and utilized systematically as bibliographic information. It is not sufficiently used in existing library big data research or cases, and there is a risk of disappearing when the website is reorganized or the person in charge is changed. This study developed a data schema that can be used in conjunction with bibliographic data by collecting and analyzing cultural programs and community service data produced in an unstructured manner and proposed to share and utilize public library cultural programs and community service data, and establish a library big data platform that can serve as an information channel between librarians who are cultural program planners. Library program data posted on the library website can be integrated and managed through the platform, securing continuity of work, and systematically managing and preserving the specialized service history of individual libraries.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.290-296
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• 2022

Big Data is a data analysis technology empowered by late advances in innovations and engineering. In any case, big data involves a colossal responsibility of equipment and handling assets, making reception expenses of big data innovation restrictive to little and medium estimated organizations. Cloud computing offers the guarantee of big data execution to little and medium measured organizations. Big Data preparing is performed through a programming worldview known as MapReduce. Normally, execution of the MapReduce worldview requires organized joined stockpiling and equal preparing. The computing needs of MapReduce writing computer programs are frequently past what little and medium measured business can submit. Cloud computing is on-request network admittance to computing assets, given by an external element. Normal arrangement models for cloud computing incorporate platform as a service (PaaS), software as a service (SaaS), framework as a service (IaaS), and equipment as a service (HaaS).

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.655-661
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• 2023

Big data, an important element of the 4th industrial revolution, is actively opening public data in public institutions and local governments. In the public data portal, everyone can conveniently search for data and check related data, but only those in ICT-related fields are using public data. Although data held by public institutions is open to citizens, it is difficult for anyone to easily utilize public data to develop applications. In this paper, data provided in open API format from public data portals has XML and JSON formats. In this study, we are a method of modularizing public data in XML format into a part that can be easily developed by linking it to a GUI interface. Based on the necessary public data, we propose a way to easily develop mobile programs and promote the use of public data.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.87-92
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• 2014

We have noted a possibility of big data as a solution of social problem and pending issue. At the same time big data has a problem of privacy. Big data and privacy were in conflict. In this paper we pointed out that issue and propose a planning of big data based on privacy using case study of advanced country.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.1
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• pp.271-287
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• 2017

This study aims to conduct a big data analysis of public library operations and uses of 16 metropolitan local government of Korea by using the Chernoff face method. This study is the first to use the Chernoff face method for big data analysis of library services in library and information research. The association of variables and human facial features was decided by survey. The study reveals that in general the provincial governments in Korea operate more libraries, invest more budgets, allocate more staff and hold more collections than metropolitan cities. This administration resulted in more use of libraries in provincial governments than metropolitan cities.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.527-535
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• 2017

As interest increases in health promotion through sports, demand for public sports facilities is steadily growing. However, there is a lack of research on operation and management compared with the supply plan of public sports facility. In this context, the aim of this study is to address problems of management of public sports centers and suggest strategies for vitalizing the facilities through the big-data. The data are collected from web such as news, blog, and cafe for one year in 2015. From the big-data, We can find that the national sports centers and the open gyms showed similar users' behavior but showed different needs. Both facilities have been used as sports and leisure area and have a high percentage of visitors for other purposes such as walking, picnics, etc. However, while the national sports facilities which were used for more specialized programs, the open sports center were used as leisure space.

• The Korean Journal of Archival Studies
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• no.67
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• pp.99-138
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• 2021

In the era of big data, analyzing not only structured data but also unstructured data is emerging as an important task. Official documents produced by government agencies are also subject to big data analysis as large text-based unstructured data. From the perspective of internal work efficiency, knowledge management, records management, etc, it is necessary to analyze big data of public documents to derive useful implications. However, since many of the public documents currently held by public institutions are not in open format, a pre-processing process of extracting text from a bitstream is required for big data analysis. In addition, since contextual metadata is not sufficiently stored in the document file, separate efforts to secure metadata are required for high-quality analysis. In conclusion, the current official documents have a low level of machine readability, so big data analysis becomes expensive.