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

• The Journal of the Korea Contents Association
• /
• v.21 no.3
• /
• pp.282-300
• /
• 2021

The purpose of this study was to explore what social media posts tell us about family life during the COVID-19 pandemic by examining the keywords and topics underlying posts on blogs and online forums. Our criteria for web crawling were (a) blog and forum posts on Naver and Daum, the top portal sites in Korea, (b) posts between February 23 and April 19, 2020, the period of the first heightened social distancing orders, and (c) inclusion of "COVID" and "family" or "COVID" and "home." We analyzed 351,734 posts using TF-IDF values and topic modeling based on latent Dirichlet allocation. We identified and named 22 topics including COVID-19 prevention, family infection, family health, dietary life and changes, religious life, stuck at home, postponed school year, family events, travel and vacations, concerns about family and friends, anxiety and stress, disaster and damage, COVID-19 warning text messages, family support policies, Shin-cheon-ji and Daegu. The results show that COVID-19 impacted various domains of family life including health, food, housing, religion, child care, education, rituals, and leisure as well as relationships and emotions.

• The Journal of Bigdata
• /
• v.7 no.1
• /
• pp.139-171
• /
• 2022

Big Data and the fourth industrial revolution are the first revolution that has not spawned a new form of energy but has triggered a new technological phenomenon called digitization. Digital transformation has caused disruptive innovation, and each country and major corporations need to respond to it. Despite this importance, empirical studies at home and abroad are insufficient. Therefore, in this study, factors affecting the promotion of corporate digital transformation were discovered through literature review, and a research model was developed and empirically analyzed by modifying and supplementing it through a Delphi study. The research model was composed of the main standards such as technology, innovation, organization, and environment and 17 sub-standards by combining the IDT and TOE models. In order to empirically analyze this, the AHP decision-making technique was used for experts in domestic digital transformation promotion companies and business partners. Companies that promote digital transformation will be able to increase the chances of achieving successful digital transformation if they take into account the factors that influence the digital transformation promotion according to the characteristics of the type of industry and company size of the group to which the company belongs.

• Journal of Internet Computing and Services
• /
• v.21 no.4
• /
• pp.97-107
• /
• 2020

This study aims to conduct a comprehensive meta-study from the perspective of content analysis to explore trends in Korean academic research on the sharing economy by using the big data analytics. Comprehensive meta-analysis methodology can examine the entire set of research results historically and wholly to illuminate the tendency or properties of the overall research trend. Academic research related to the sharing economy first appeared in the year in which Professor Lawrence Lessig introduced the concept of the sharing economy to the world in 2008, but research began in earnest in 2013. In particular, between 2006 and 2008, research improved dramatically. In order to grasp the overall flow of domestic academic research of trends, 8 years of papers from 2013 to the present have been selected as target analysis papers, focusing on titles, keywords, and abstracts using database of electronic journals. Big data analysis was performed in the order of cleaning, analysis, and visualization of the collected data to derive research trends and insights by year and type of literature. We used Python3.7 and Textom analysis tools for data preprocessing, text mining, and metrics frequency analysis for key word extraction, and N-gram chart, centrality and social network analysis and CONCOR clustering visualization based on UCINET6/NetDraw, Textom program, the keywords clustered into 8 groups were used to derive the typologies of each research trend. The outcomes of this study will provide useful theoretical insights and guideline to future studies.

• The Journal of the Korea Contents Association
• /
• v.16 no.6
• /
• pp.260-269
• /
• 2016

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. Also, oriental medicine research is focused with modern research technology and validate it's various biochemical effect by combining with molecular biology technology. However there are few searching system for finding biochemical mechanism which is related to major compounds in oriental medicine. Therefore, in this paper, we collected papers related with medical herbs from PubMed and constructed a medical herbs database to store and manage chemical, gene/protein and biological interaction information extracted by a literature analysis on the papers. Also, to supporting a multidimensional analysis on the database, we developed a network analysis system based on a hierarchy structure of chemical, gene/protein and biological interaction information. Finally, we expect this system will be used the major tool to discover various biochemical effect by combining with molecular biology technology.

• The Journal of the Korea Contents Association
• /
• v.21 no.8
• /
• pp.367-375
• /
• 2021

The quality of medical care can be defined as four types such as effectiveness, efficiency, adequacy, and scientific-technical quality. For the management of scientific-technical aspects, medical institutions annually disseminate the latest knowledge in the form of conservative education. However, there is an obvious limit to the fact that the latest knowledge is distributed quickly enough to the clinical site with only one-time conservative education. If intelligent information processing technologies such as big data and artificial intelligence are applied to the medical field, they can overcome the limitations of having to conduct research with only a small amount of information. In this paper, we construct databases on which the existing medicine prescription adaptations can be extended. To do this, we collect, store, manage, and analyze information related to oriental medicine at domestic and abroad Journals. We design a processing and analysis technique for oriental medicine evidence research data for the construction of a database of oriental medicine prescription extended adaption. Results can be used as a basic content of evidence-based medicine prescription information in the oriental medicine-related decision support services.

• Proceedings of the Korea Contents Association Conference
• /
• 2017.05a
• /
• pp.27-28
• /
• 2017

다양한 위상학적 관계(topological relation)를 분석하는 네트워크 분석은 복잡한 데이터에서 숨어있는 특성과 사실을 발견하는 기술로 최근 빅데이터 분야에서 데이터 분석 핵심 기술로 급부상하고 있다. 본 연구에서는 질병연구에 핵심적인 생물학적 네트워크의 생성 및 사용자 친화적인 네트워크 분석시스템을 개발하였다. 개발한 시스템은 PubMed에서 특정 질병과 관련있는 논문 요약 정보를 자동 수집후 텍스트마이닝을 통해 질병 관련 화합물, 유전자 그리고 상호작용 정보를 추출해 생물학적 네트워크를 생성하는 기능을 제공한다. 또한, 연구자가 손쉽게 생성된 네트워크에 대한 검색 및 다차원 분석을 수행할 수 있는 기능을 제공한다. 마지막으로 개발한 시스템의 우수성을 입증하기 위해 크론병(Crohn's Disease)에 대한 적용사례를 소개한다.

• Journal of the Korean Society for information Management
• /
• v.41 no.1
• /
• pp.107-132
• /
• 2024

This study attempted to analyze newspaper articles related to May 18 through frequency analysis and network analysis using news data related to May 18 for about 30 years from 1990 to 2022 at the Korea Press Foundation's Big Kinds. Specifically, quantitative change trends were examined by analyzing the amount of articles by period and region, and the connection structure between major keywords by the regime was explored through network analysis by regime using co-appearance keywords. As a result of the analysis, it was found that 2019 had the largest amount of coverage, which had many social issues in time, and the Jeolla-do region had the largest amount of coverage in the region. And as a result of network analysis, there were differences in words related to May 18 in news data according to the perception and policy of the regime toward May 18. As a result of synthesizing the analysis of May 18 news data, it was confirmed that May 18 was becoming a democratic movement over time regardless of region, but at the same time, the distortion of May 18 was not resolved.

• The Korean Journal of Archival Studies
• /
• no.70
• /
• pp.85-117
• /
• 2021

The purpose of this study is to investigate and analyze the current status of unit tasks, unit task operation, and record management problems used by local governments, and to present improvement measures using text-based big data technology based on the implications derived from the process. Local governments are in a serious state of record management operation due to errors in preservation period due to misclassification of unit tasks, inability to identify types of overcommon and institutional affairs, errors in unit tasks, errors in name, referenceable standards, and tools. However, the number of unit tasks is about 720,000, which cannot be effectively controlled due to excessive quantities, and thus strict and controllable tools and standards are needed. In order to solve these problems, this study developed a system that applies text-based analysis tools such as corpus and tokenization technology during big data analysis, and applied them to the names and construction terms constituting the record management standard. These unit task operation support tools are expected to contribute significantly to record management tasks as they can support standard operability such as uniform preservation period, identification of delegated office records, control of duplicate and similar unit task creation, and common tasks. Therefore, if the big data analysis methodology can be linked to BRM and RMS in the future, it is expected that the quality of the record management standard work will increase.

• Journal of Service Research and Studies
• /
• v.8 no.1
• /
• pp.73-87
• /
• 2018

Countries around the world are preparing policies to promote service economy. Recently, as the fourth industrial revolution is accelerating, interest in the service industry is increasing. Korea's service industry is among the lowest among OECD countries in terms of employment, value-added and productivity, and it is time to explore new development strategies. The Korean government is establishing a service economic development strategy to promote employment and economic vitality. However, in the era of the 4th industrial revolution, the service industry is very important in that it has to be fused with the manufacturing industry. This study examines the service industry policy related to the 4th industrial revolution which the central government, local governments, and countries around the world are pursuing through literature review. The Big data analysis is used to determine the interest rate of the seven major service industries and core technologies for the fourth generation industrial revolution.