• Title/Summary/Keyword: 문헌 빅데이터

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Forecasting Market trends of technologies using Bigdata (빅데이터를 이용한 기술 시장동향 예측)

  • Mi-Seon Choi;Yong-Hwack Cho;Jin-Hwa Kim
    • Journal of Industrial Convergence
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    • v.21 no.10
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    • pp.21-28
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    • 2023
  • As the need for the use of big data increases, various analysis activities using big data, including SNS data, are being carried out in individuals, companies, and countries. However, existing research on predicting technology market trends has been mainly conducted using expert-dependent or patent or literature research-based data, and objective technology prediction using big data is needed. Therefore, this study aims to present a model for predicting future technologies through decision tree analysis, visualization analysis, and percentage analysis with data from social network services (SNS). As a result of the study, percentage analysis was better able to predict positive techniques compared to other analysis results, and visualization analysis was better able to predict negative techniques compared to other analysis results. The decision tree analysis was also able to make meaningful predictions.

Trend Analysis of Convergence Research based on Social Big Data (소셜 빅데이터 기반 융합연구 동향 분석)

  • Noh, Younghee;Kim, Taeyoun;Jeong, Dae-Keun;Lee, Kwang Hee
    • The Journal of the Korea Contents Association
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    • v.19 no.2
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    • pp.135-146
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    • 2019
  • This study was designed to analyze trends in the entire convergence research beyond academic research through social media big data analysis at a time when interdisciplinary convergence research is emphasized along with the fourth industrial revolution. For this purpose, about 150,000 cases of texts and titles were acquired for about 10 years from January 2009 to September 2018 in connection with the convergence research in social media, and word cloud and network analysis were conducted. As a results, the research fields that were actively conducted for each period were eco-tech in 2009 and 2010, smart technology in 2011 and 2012, information and communication in 2013 and 2014, robots in 2015 and 2016, and artificial intelligence in 2017 and 2018. Also, the research areas that have been consistently conducted for about 10 years are culture, design, chemistry, nanotechnology, biotechnology, robot, IT, and information and communication. Since this study identifies trends in convergence research over time, it can be helpful to researchers who are planning convergence research direction by understanding the trends of convergence research.

A Review of Influencing Aronia Intake on Human Body in Korea (국내 아로니아 습취가 인체에 미치는 영향에 관한 문헌분석)

  • Nam, Soo-Tai;Yu, Ok-Kyeong;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.149-152
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    • 2017
  • Big data analysis is an effective analysis techniques of unstructured data such as internet, social network services, web documents generated in mobile environment, e-mail, and social data, as well as formal data well organized in the database. Thus, meta-analysis is a statistical integration method that delivers an opportunity to overview the entire result of integrating and analyzing many quantitative research results. Today, regardless of gender and age is increasing interest in whether you can lead a younger and healthier life. With this change of life which has been developed with a variety of functional health food. Aronia melanocarpa called black chokeberry is a fruit of berry plants belonging to the Rosaceae originally growing in the North America region. In the studies for factors related to quality characteristics and antioxidant activities as the extracts of Aronia in this study, which it is only targeted factors as total sugar, acidity, polyphenol, anthocyanin, antioxidant. Thus, we present the theoretical and practical implications of these results.

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A Study on Regional-customizededucation program selection model using big data analysis (빅데이터 분석을 활용한 지역 맞춤형 교육프로그램 선정 모형 개발)

  • Hyeon-Seong Kim;Jin-Sook Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.2
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    • pp.381-388
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    • 2023
  • This thesis is purposed to develop a regional-customized education program selection model using big data analysis. Based on the literature review, the concepts and characteristics of big data and lifelong education are analyzed. In addition, this thesis presents how to collect the data for lifelong education and to use big data suitable for the characteristics of lifelong education. Based on these results, a regional- customized lifelong education program selection model is developed. The regional customized lifelong education program model is developed by the following six steps. The customized education program model proposed in this study has a high degree of flexibility in terms of practical use, as it can be utilized in real-time data provision methods such as the nationally approved Lifelong Learning Personal Status Survey without the need for analysis one year later, allowing for selective analysis and future predictions. It is clear that there is a significant need and value for big data in the education field. Furthermore, all programs used in the sample model are provided free of charge, and due to the programming nature, the community is actively engaged in exchanges, making it very easy to modify and improve for the development of a more complete education program model in the future.

A Literature Review on Information Visualization of Manufacturing Industry Sector (제조업 분야의 정보시각화 문헌연구)

  • Chang, Tai-Woo
    • The Journal of Society for e-Business Studies
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    • v.21 no.1
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    • pp.91-104
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    • 2016
  • Business intelligence based on the data analysis come into the spotlight. Especially, information visualization of the analysis result is treated significantly. given the interest in big data technologies. Because corporate managers want to use the results of data analysis in the decision-making process and the visualization technology will give help with cognitive function and operation function. In this paper, the status of information visualization is reviewed and analyzed from the viewpoint of manufacturing service. Several implications are drawn and it is expected that they will help to developers and administrators of manufacturing sector who want to adopt information visualization applications.

The Utilization of Big Data's Disaster Management in Korea (국내 재난관리 분야의 빅 데이터 활용 정책방안)

  • Shin, Dong-Hee;Kim, Yong-Moon
    • The Journal of the Korea Contents Association
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    • v.15 no.2
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    • pp.377-392
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    • 2015
  • In today's data-driven society, we've been hearing a great deal about the power of Big Data over the last couple of years. At the same time, it has become the most important issue that the problems is caused by the data collection, management and utilization. Moreover, Big Data has a wide applications ranging from situation awareness, decision-making to the area to enable for the foreseeable future with man-made and analysis of data. It is necessary to process data into meaningful information given that the huge amount of structured and unstructured data being created in the private and the public sector, even in disaster management. This data should be public and private sector at the same time for the appropriate linkage analysis for effective disaster management. In this paper, we conducted a literature review and case study efficient Big Data to derive the revitalization of national disaster management. The study obtained data on the role and responsibility of the public sector and the private sector to leverage Big Data for promotion of national disaster management plan. Both public and private sectors should promote common development challenges related to the openness and sharing of Big Data, technology and expansion of infrastructure, legal and institutional maintenance. The implications of the finding were discussed.

Subject Association Analysis of Big Data Studies: Using Co-citation Networks (빅데이터 연구 논문의 주제 분야 연관관계 분석: 동시 인용 관계를 적용하여)

  • Kwak, Chul-Wan
    • Journal of the Korean Society for information Management
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    • v.35 no.1
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    • pp.13-32
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    • 2018
  • The purpose of this study is to analyze the association among the subject areas of big data research papers. The subject group of the units of analysis was extracted by applying co-citation networks, and the rules of association were analyzed using Apriori algorithm of R program, and visualized using the arulesViz package of R program. As a result of the study, 22 subject areas were extracted and these subjects were divided into three clusters. As a result of analyzing the association type of the subject, it was classified into 'professional type', 'general type', 'expanded type' depending on the complexity of association. The professional type included library and information science and journalism. The general type included politics & diplomacy, trade, and tourism. The expanded types included other humanities, general social sciences, and general tourism. This association networks show a tendency to cite other subject areas that are relevant when citing a subject field, and the library should consider services that use the association for academic information services.

Strategies for College Entrance Based on Big Data Analysis -Case Study of college in Central Region- (빅데이터 분석에 기반한 대학 입시홍보 -중부권 전문대학교 사례-)

  • Bae, Jungho;Burm, Eunae
    • Journal of Internet of Things and Convergence
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    • v.8 no.2
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    • pp.25-33
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    • 2022
  • The purpose of this study is to provide the basic data for establishing a unique admissions promotion strategy for each university and to innovate the paradigm of university admissions promotion through the examples of central universities in the practice of PR promotion based on big data analysis. To this end, prior literature related to university publicity (marketing), and recognition of prospective college students who visited the university, and database data were defined and analyzed as big data. As a result, first, the preliminary studies related to college entrance exam promotion (marketing) increased dramatically in the 2000s and 2010s as part of preparing for countermeasures against population decline in school age. Responding to the need for an admissions promotion strategy to accelerate visits to prospective college students, the database data analysis result suggested the selection and concentration of entrance exam strategies based on the university's regional and academic characteristics.

A Study on the Contemporary Definition of 'GARDEN' - Keyword Analysis used Literature Research and Big Data - ('정원'의 시대적 정의에 관한 연구 - 문헌연구와 빅데이터를 활용한 키워드 분석을 중심으로-)

  • Woo, Kyungsook;Suh, Joo Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.44 no.5
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    • pp.1-11
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    • 2016
  • There has been an increasingly high interest in gardens and garden design in Korea recently. However, the usage of the term 'garden' is extremely varied and complex, and there has been very little academic research made on the meaning of garden. Therefore, this research attempts to investigate the ideas of current gardens and to elucidate their changing patterns by means of extensive literature research and big data analysis. The notion of garden in the past was broad including not only private space such as Madang(마당) and Teul(뜰), but also even field and grass land as public outdoor space. Yet, the meaning has become smaller to merely private space due to the change of dwelling systems due to high industrial development of the 20th century. Furthermore, the introduction of urban parks as an interactive space between nature and humans, the similar spatial function of gardens, has blurred the boundary between garden and park, which created confusion in understanding the concept of a garden. After all, garden is a subject for humans. The meanings of garden need to be recognized from various points of view since garden itself is a creation by the sum of diverse fields such as natural and social sciences as well as culturology. This discussion on the meaning of garden in the present day will give a conceptual foundation for future research on gardens and garden design. Also, the big data analysis employed here as a research method can help other similar research topics, particularly semantics in landscape architecture.

An Analysis of News Media Coverage of the QRcode: Based on 2008-2023 News Big Data (QR코드에 대한 언론 보도 경향: 2008-2023년 뉴스 빅데이터 분석)

  • Sunjeong Kim;Jisu Lee
    • Journal of the Korean Society for information Management
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    • v.41 no.2
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    • pp.269-294
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    • 2024
  • This study analyzed the news media coverage of QRcodes in Korea over a 16-year period (2008 to 2023). A total of 13,335 articles were extracted from the Korea Press Foundation's BigKinds. A quantitative and content analysis was conducted on the news frames. The results indicated that the quantity of news coverage has increased. The greatest quantity of news coverage was observed in 2020, and the most frequently discussed topic in the news was 'IT_Science'. The results of the keyword analysis indicated that the primary words were 'QRcode', 'smartphone', 'service', 'application', and 'payment'. The news media primarily focused on the QRcode's ability to provide instant access and recognition technology. This study demonstrates that advanced information and communication technologies and the increased prevalence of mobile devices have led to a rise in the utilization of QRcodes. Furthermore, QRcodes have become a significant information media in contemporary society.