• Title/Summary/Keyword: Big Data Utilization

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A Study of Ginseng Culture within 'Joseonwangjosilok' through Textual Frequency Analysis

  • Mi-Hye Kim
    • CELLMED
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    • v.14 no.2
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    • pp.2.1-2.10
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    • 2024
  • Through big data analysis of the 'Joseonwangjosilok', this study examines the perception of ginseng among the ruling class and its utilization during the Joseon era. It aims to provide foundational data for the development of ginseng into a high-value cultural commodity. The focus of this research, the Joseonwangjosilok, comprises 1,968 volumes in 948 books, spanning a record of 518 years. Data was collected through web crawling on the website of the National Institute of Korean History, followed by frequency analysis of significant words. To assess the interest in ginseng across the reigns of 27 kings during the Joseon era, ginseng frequency records were adjusted based on years in power and the number of articles, creating an interest index for comparative rankings across reigns. Analysis revealed higher interest in ginseng during the reigns of King Jeongjo and King Yeongjo in the 18th century, King Sunjo in the 19th century, King Sejong in the 15th century, King Sukjong in the 17th century, and King Gojong in the 19th century. Examining the temporal emergence and changes in ginseng during the Joseon era, general ginseng types like insam and sansam had the highest frequency in the 15th century. It appears that Korea adeptly utilized ceremonial goods in diplomatic relations with China and Japan, meeting the demand for ginseng from their royal and aristocratic societies. Processed ginseng varieties such as hongsam and posam, along with traded and taxed ginseng, showed peak frequency in the 18th century. This coincided with increased cultivation, allowing a higher supply and fostering the development of ginseng processing technologies like hongsam.

Utilization of R Program for the Partial Least Square Model: Comparison of SmartPLS and R (부분최소제곱모형을 위한 R 프로그램의 활용: SmartPLS와 R의 비교)

  • Kim, Yong-Tae;Lee, Sang-Jun
    • Journal of Digital Convergence
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    • v.13 no.12
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    • pp.117-124
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    • 2015
  • As the acceptance of statistical analysis has been increased because of Big Data, the needs for an advanced second generation of statistical analysis method like Structural Equation Model are also increasing. This study suggests how R-Program, as open software, can be utilized when Partial Least Square Model, one of the SEMs, is applied to statistical analysis. R is a free software as a part of GNU projects as well as a powerful and useful tool for statistical analysis including Big Data. The study utilized R and SmartPLS, a representative statistical package of PLS-SEM, and analyzed internal consistency reliability, convergent validity, and discriminant validity of the measurement model. The study also analyzed path coefficients and moderator effects of the structural model and compared the results, respectively. The results indicated that R showed the same results with SmartPLS on the measurement model and the structural model. Therefore, the study confirmed that R could be a powerful tool that is alternative to a commercial statistical package in the future.

Quality Strategy in the Age of the 4th Industrial Revolution by Technological Evolution (기술 발전에 따른 4차 산업혁명 시대의 품질 전략)

  • Chong, Hye Ran;Hong, Sung Hoon;Lee, Min Koo;Kwon, Hyuck Moo
    • Journal of Korean Society for Quality Management
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    • v.46 no.3
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    • pp.483-496
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    • 2018
  • Purpose: This paper proposes a quality strategy based on the evolution of technology in the age of the 4th Industrial Revolution. Methods: We examine the theory of past quality activities and the changes in quality paradigm, and analyze key words for the technologies and key issues of the 4th Industrial Revolution. Based on existing quality management, we find a quality strategy that should be pursued during the 4th Industrial Revolution. Results: Quality has been recognized as an essential component of corporate competitiveness. The paradigm of quality has also changed with the pass of time and industry development. From this viewpoint, the following eight quality strategies are proposed for the development of the technology of the 4th Industrial Revolution period, such as Market-to-customer fusion quality, symbiotic quality, big data quality, technical accuracy and zero-defect quality, facility predictability quality, software quality, process flexibility quality, and information protection stability and security quality. Conclusion: Quality for customer satisfaction is still important nowadays. However, in the 4th Industrial Revolution era, where various business models and methods of manufacturing are expected, the big data utilization, software quality, and the reliability and security of information protection to support it are important.

A Study on the Introduction of Intelligent Document Processing and Change of Record Management (지능형 문서처리 도입과 기록관리 변화에 관한 연구)

  • Ryu, Hanjo;Lee, Kyungnam;Hwang, Jinhyun;Yim, Jinhee
    • The Korean Journal of Archival Studies
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    • no.68
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    • pp.41-72
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    • 2021
  • In order to analyze big data, documents should be converted to a open standard format to increase machine readability. It also need natural language processing tools. This study focused on the background of intelligent document processing and the status of research in the public sector, and predicted the changes in work that intelligent document processing would bring. This study noted the changes that intelligent document processing would bring to the archival work, and also considered changes in the role of archivist and their required competencies. Changes in archival work could be anticipated across a wide range of Records Management work and Archives Management work. In particular, it was expected to have a significant impact on the automation of repetitive archival tasks or the description and utilization of records. This study proposed the need to prepare new archival work procedures, methods, and necessary competencies in response to these change in archival work.

An Analysis of Policy and Technology Status of Smart City for Revitalization of Smart City Industry (스마트도시 산업 활성화를 위한 스마트도시 정책 및 기술현황 분석에 관한 연구)

  • Kim, Dae Ill;Park, Sung Chan;Yeom, Chun Ho
    • Journal of Information Technology Services
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    • v.21 no.1
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    • pp.127-144
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    • 2022
  • Recently, Korea is promoting cooperation with various countries, centering on ASEAN countries, with the aim of exporting Korean smart cities for the globalization of smart cities. The purpose of this study is to select excellent smart city technologies through analysis of smart city technologies owned by domestic companies and company status, and to prepare a plan for revitalization of companies with smart city technologies. Through prior research, the implications were derived through research on the existing smart city. Next, established a smart city policy analysis and smart city technology classification criteria through Korea and Overseas smart city policy and Korea smart city technology status DB. And the big data of smart city technology possessed by Korea companies and a plan for selecting a smart city export technology was prepared through analysis by region and company. As a result, to activate the technology possessed by Korea companies and to export overseas, it seems to need financial support and tax incentives that secure a pathway to export specialized smart technologies of SMEs, along with citizen participation and institutional supplementation. The smart city technology fields with the highest utilization in Korea were traffic, green energy, e-government, crime prevention, and construction, and the service types were platform, IoT, AI, big data, and GIS/GPS. These technologies are expected to contribute to building a platform for overseas smart city technology exports.

Analysis of Work-Related Musculoskeletal Disorders Research Trends Using Keyword Frequency Analysis and CONCOR Technique

  • Geon-Hui Lee;Seo-Yeon Choi
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.8
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    • pp.137-144
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    • 2023
  • One of the methods being suggested as a way to address social issues is the utilization of big data analysis techniques. In this study, we utilized keyword network analysis and CONCOR analysis techniques to analyze the research trends on work-related musculoskeletal disorders. The findings of this study are as follows: Firstly, the number of papers on work-related musculoskeletal disorders has been consistently increasing, with an average of over 33 articles published per year since the investigation of musculoskeletal risk factors in 2003. The publication rate showed an increase from 2007 to 2009. Secondly, the frequency of the top keywords identified through text mining were as follows: work (4,940), musculoskeletal disorders (2,197), symptoms (1,836), related (1,769), musculoskeletal system (1,421). Thirdly, the CONCOR analysis resulted in the formation of four clusters: ' Musculoskeletal disorder treatment', 'Occupational health and safety management', 'Work environment assessment', and ' Workplace environment measurement'. It is expected that this study will contribute to the development of research on musculoskeletal disorders and provide various directions for future studies.

Study of Policy on Seowon's Preservation·Support : Focusing on Big Data Analysis on Laws (한국 서원의 보존·지원 정책에 관한 연구 : 법률에 대한 빅데이터 분석을 중심으로)

  • Bang, Mee Young
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.875-883
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    • 2023
  • In Korea, the number of preservation and management entities to connect the traditional cultural heritage to next generations is rapidly decreasing. Building an infrastructure to pass on traditional cultural heritage to the next generation and to pay attention to the preservation and management of the next generation is important including the 'Seowon', a World Cultural Heritage listed by UNESCO. This study is based on the laws that regulates the preservation and support of traditional cultural assets and 'Seowon, through Big Data analysis techniques. The main keywords in each law were extracted, schematized, and a mutual Word Network was constructed and policy advice was derived. As policy advice, it is necessary to establish and implement policies to nurture and support businesses specialized in the region for the preservation·utilization, preservation·management and preservation·support of Seowons.

Big Data Analysis for Strategic Use of Urban Brands: Case Study Seoul city brand "I SEOUL U" (도시 브랜드의 전략적 활용을 위한 빅데이터 분석 : 서울시 도시 브랜드 "I SEOUL U" 사례)

  • Lim, Haewen
    • The Journal of the Korea Contents Association
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    • v.22 no.1
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    • pp.197-213
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    • 2022
  • In this study, text mining analysis was performed on online big data for recognition and assessment of urban brand I Seoul U. To this end, TEXTOM, a processing program for data acquisition and analysis was used, and the 'I SEOUL U' keyword was selected as an analysis keyword. Keyword analysis shows the keywords associated with I Seoul U to be as follows: First, as a business and marketing term, keywords include pop-up store, gallery, co-branding, (festival, etc.), commodities, private companies and online. Second, as an event-related term, keywords include Han River, tree-planting day, tree planting, Hongdae, Christmas, Mapo, Jung-gu, Sejong University, and festival. Third, as a promotional term, keywords include robotics engineer Dr. Dennis Hong, Government, Art and Korea. In the N Gram analysis, as the city brand of Seoul, I Seoul U, in the public interest, was found to contribute to the commercial activities of private companies. In connection-oriented analysis, business and marketing, events, and promotions have been derived as categories. In matrix analysis, it was found that the products of the pop-up store are mainly developed, and products in the form of co-branding were being developed. In the topic modeling, a total of 10 topics were extracted and needs for commercial utilization and information for event festivals were mostly found.

A Study on Public Awareness of Landslide and Check Dam Using the Big Data Platform 'Hyean' (공공 빅데이터 플랫폼 '혜안'을 통한 산사태 및 사방댐 인식 분석)

  • Sohee Park;Min Jeng Kang;Song Eu
    • Journal of the Society of Disaster Information
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    • v.18 no.4
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    • pp.687-698
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    • 2022
  • Purpose: This study was conducted to understand the public awareness of landslide and check dams in 2015-2020 using the big data platform 'Hyean' and to confirm the utilization of this platform in disaster prevention areas. Method: The total amount, number of detection by period by media, and affirmative and negative trends of a search for 'landslide' and 'check dam' in 2015-2020 were analyzed using a keyword search of 'Hyean.' Result: There is significant lack of public awareness of check dam compared to landslide, and the trend is more noticeable in the conspicuous gap of data amount between the news and SNS media. The number and the timing of the search for 'landslide' coincided with the actual occurrence of landslide, while the detection of 'check dam' was less related to it. Relatively affirmative preception for the check dam is inferred, but it was difficult to confirm accurate statistical affirmative and negative trends in the disaster prevention field using 'Hyean.' Conclusion: Unlike the experts who expect positive public awareness of check dam, the statistic results show that the public awareness of the check dam as an effective countermeasure against landslide was extremely low. Active promotion of erosion control projects should be carried out first, and a balanced sample survey should accompany online and periodic field surveys. Since there is a limit to grasping the effective perception in the field of disaster prevention area using 'Hyean', it should be very cautious to establish local/governmental policies using it.

Draft Design of AI Services through Concept Extension of Connected Data Architecture (Connected Data Architecture 개념의 확장을 통한 AI 서비스 초안 설계)

  • Cha, ByungRae;Park, Sun;Oh, Su-Yeol;Kim, JongWon
    • Smart Media Journal
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    • v.7 no.4
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    • pp.30-36
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    • 2018
  • Single domain model like DataLake framework is in spotlight because it can improve data efficiency and process data smarter in big data environment, where large scaled business system generates huge amount of data. In particular, efficient operation of network, storage, and computing resources in logical single domain model is very important for physically partitioned multi-site data process. Based on the advantages of Data Lake framework, we define and extend the concept of Connected Data Architecture and functions of DataLake framework for integrating multiple sites in various domains and managing the lifecycle of data. Also, we propose the design of CDA-based AI service and utilization scenarios in various application domain.