• Journal of Digital Convergence
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• v.20 no.3
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• pp.317-323
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• 2022

The purpose of this study was to analyze how innovative facility investment and innovative research manpower capabilities of venture companies related to the 4th industrial smart farm affect the technological performance of patents and design registrations, and the financial performance of sales and operating profit. As a research method, a total of 47 venture companies were selected as a sample and regression analysis was performed. Research Results This study analyzes the technological commercialization factors of venture companies related to the 4th industrial smart farm and proposes to expand the budget for R&D government tasks for financial and technological success. In the future research direction, I believe that more discussion is needed on the contribution of companies to quantitative and qualitative growth.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.655-662
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• 2023

Big data research plays a role of supplementing existing social science research methods. If the survey and experimental methods are somewhat inaccurate because they mainly rely on recall memories, big data are more accurate because they are real-time records. Social science research so far, which mainly conducts sample research for reasons such as time and cost, but big data research analyzes almost total data. However, it is not easy to repeat and reproduce social research because the social atmosphere can change and the subjects of research are not the same. While social science research has a strong triangular structure of 'theory-method-data', big data analysis shows a weak theory, which is a serious problem. Because, without the theory as a scientific explanation logic, even if the research results are obtained, they cannot be properly interpreted or fully utilized. Therefore, in order for big data research to become a methodological innovation, I proposed big thinking along with researchers' efforts to create new theories(black boxes).

• Journal of Society of Preventive Korean Medicine
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• v.27 no.3
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• pp.1-12
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• 2023

Objectives : The aim of this study is to analyze the news articles related to Korean Medicine(KM) and compare trends in news reports from 2018 to 2022. Method : News articles related to KM were collected through the BigKinds, the news bigdata service of the Korea Press Foundation. News reports from 1 January 2018 to 31 December 2022 were searched. 2,950 news articles out of a total of 12,497 met the inclusion criteria. First, quantitative changes in media coverage were analyzed by year, media outlet, and month. For qualitative analysis, two authors independently coded the content of news articles, discussed them until consensus, and consulted with a third researcher to classify them. In addition, keywords extracted by the BigKind's Topic Rank algorithm were compared and analyzed in each year. Results : The number of news articles on KM decreased by 42% in 2022 compared to 2018. Over a fiveyear period, the Naeil Shinmun reported the most on KM among newspapers, while the Hankyoreh did the least. Among broadcasters, YTN reported the most and SBS did the least. When analyzing the reports by category, the most common was 'treatment', followed by 'prevention' and 'scientification'. As a result of extracting keywords with high weight and frequency, 'immunity' and 'immune system' ranked the first and second in 2018, while 'COVID 19' and 'medical law violation' did in 2022. Conclusion : The decrease in media reports on KM during the COVID-19 epidemic period seems to be due to the limited role of KM in responding to infectious diseases, and efforts to expand the scope of KM can induce increased media reports and social interest.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.391-396
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• 2024

This study proposes a novel reverse N-Gram approach to overcome the limitations of traditional N-Gram methods and enhance performance in building an entity dictionary specialized for the healthcare sector. The proposed reverse N-Gram technique allows for more precise analysis and processing of the complex linguistic features of healthcare-related big data. To verify the efficiency of the proposed method, big data on healthcare and digital health announced during the Consumer Electronics Show (CES) held each January was collected. Using the Python programming language, 2,185 news titles and summaries mentioned from January 1 to 31 in 2010 and from January 1 to 31 in 2024 were preprocessed with the new reverse N-Gram method. This resulted in the stable construction of a dictionary for natural language processing in the healthcare field.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.239-259
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• 2022

Since 2019, research on microplastics has been actively conducted around the world, so analyzing the differences between domestic and foreign microplastics research can be a milestone in establishing the direction of domestic research. In this study, microplastic papers from KCI and WoS were extracted and the differences between domestic and foreign studies were analyzed using a network analysis methodology based on big data such as author keyword co-occurrence word analysis, thesis co-citation analysis, and author co-citation analysis. As a result of the analysis, the analysis of the research topic confirmed that studies that could affect the human body and the treatment of microplastics in daily life were additionally needed in Korea. In the analysis of the depth of thesis citation that examines the quality of research, it was found that Korea was still insufficient at 2.25 overseas and 1.39 in Korea. In the analysis of the composition of the joint research front, where various researchers participate and share information, 3 out of 22 clusters in Korea are Star type. In the case of overseas, all 19 clusters have a mesh structure, so it was confirmed that information flow and sharing were insufficient in specific research fields in Korea. These research results confirmed the need to expand the research topic of microplastics, improve the quality of research, and improve the research promotion system in which various researchers participate. In addition, if the automation program is developed based on topic modeling, it will be possible to build a system capable of real-time analysis.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.80-93
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• 2022

This study is a study on a methodology that can extract various factors that affect purchase and use of products/services from the consumer's point of view through previous studies, and analyze the types and tendencies of consumers according to age and gender. To this end, we quantify factors in terms of general personal propensity, consumption influence, consumption decision, etc. to check the consistency of data, and based on these studies, we conduct research to suggest and prove data analysis methodologies of consumer types that are meaningful from the perspectives of startups and SMEs. did As a result, it was confirmed through cross-validation that there is a correlation between the three main factors assumed for data analysis from the consumer's point of view, the general tendency, the general consumption tendency, and the factors influencing the consumption decision. verified. This study presented a data analysis methodology and a framework for consumer data analysis from the consumer's point of view. In the current data analysis trend, where digital infrastructure develops exponentially and seeks ways to project individual preferences, this data analysis perspective can be a valid insight.

• The Journal of Bigdata
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• v.3 no.2
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• pp.87-99
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• 2018

This study analyze the factors affecting the number of bidders in public contracts by collecting contract data such as purchase of goods, service and facility construction through KONEPS among various forms of public contracts. The reason why the number of bidders is important in public contracts is that it can be a minimum criterion for judging whether to enter into a rational contract through fair competition and is closely related to the budget reduction of the ordering organization or the profitability of the bidders. The purpose of this study is to analyze the factors that determine the participation of bidders in public contracts and to present the problems and policy implications of bidders' participation in public contracts. This research distinguishes the existing sampling based research by analyzing and analyzing many contracts such as purchasing, service and facility construction of 4.35 million items in which 50,000 public institutions have been placed as national markets and 300,000 individual companies and corporations participated. As a research model, the number of announcement days, budget amount, contract method and winning bid is used as independent variables and the number of bidders is used as a dependent variable. Big data and multidimensional analysis techniques are used for survey analysis. The conclusions are as follows: First, the larger the budget amount of public works projects, the smaller the number of participants. Second, in the contract method, restricted competition has more participants than general competition. Third, the duration of bidding notice did not significantly affect the number of bidders. Fourth, in the winning bid method, the qualification examination bidding system has more bidders than the lowest bidding system.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.121-131
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• 2017

With emergence of Internet, social media, and mobile service, the consumers have actively presented their opinions and sentiment, and then it is spreading out real time as well. The user-generated text data on the Internet and social media is not only the communication text among the users but also the valuable resource to be analyzed for knowing the users' intent and sentiment. In special, economic participants have strongly asked that the social big data and its' analytics supports to recognize and forecast the economic trend in future. In this regard, the governments and the businesses are trying to apply the social big data into making the social and economic solutions. Therefore, this study aims to reveal the capability of social big data analysis for the economic use. The research proposed a social big data analysis model and an online consumer sentiment index. To test the model and index, the researchers developed an economic survey ontology, defined a sentiment dictionary for sentiment analysis, conducted classification and sentiment analysis, and calculated the online consumer sentiment index. In addition, the online consumer sentiment index was compared and validated with the composite consumer survey index of the Bank of Korea.

• The Journal of Industrial Distribution & Business
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• v.9 no.8
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• pp.51-60
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• 2018

Purpose - Civil affairs are increasing in various forms, but civil servants who are able to handle them want to reduce the complaints and provide keywords that will help in the future due to their lack of time. While various ideas are presented and implemented as policies in solving civil affairs, there are many cases that are not policies that people can sympathize with. Therefore, it is necessary to analyze the complaints accurately and to present correct solutions to the analyzed civil complaint data. Research design, data, and methodology - We analyzed the complaints data for the last three years and found out how to solve the problems of Yongin City and alleviate the burdens of civil servants. To do this, the Hadoop platform and Design Thinking process were reviewed, and proposed a new process to fuse it. The big data analysis stage focuses on civil complaints - Civil data extraction - Civil data analysis - Categorization of the year by keywords analyzing them and the needs of citizens were identified. In the forecast analysis for deriving insights, - The case of innovation case study - Idea derivation - Idea evaluation - Prototyping - Case analysis stage used. Results - Through this, a creative idea of providing free transportation cards to solve the major issues of construction, apartment, installation, and vehicle problems was discovered. There is a specific problem of how to provide these services to certain areas, but there is a pressing need for a policy that can contribute as much as it can to the citizens who are suffering from various problems at this moment. Conclusions - In the past, there were many cases in which free traffic cards were issued mainly to the elderly or disabled. In other countries, foreign residents of other area visit the areas for accommodation, and may give out free transportation cards as well. In this case, the local government will be able to set up a framework to present with a win-win scenario in various ways. It is necessary to reorganize the process in future studies so that the actual solution will be adopted, reduce civil complaints, help establish policies in the future, and be applied in other cities as well.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.79-86
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• 2021

In order to increase the probability of success in big data projects, quantified techniques are required to analyze the root cause of risks from complex causes and establish optimal countermeasures. To this end, this study measures risk factors and relationships through SNA analysis and presents a way to respond to risks based on them. In other words, it derives a dependency network matrix by utilizing the results of correlation analysis between risk groups in the big data projects presented in the preliminary study and performs SNA analysis. In order to derive the dependency network matrix, partial correlation is obtained from the correlation between the risk nodes, and activity dependencies are derived by node by calculating the correlation influence and correlation dependency, thereby producing the causal relationship between the risk nodes and the degree of influence between all nodes in correlation. Recognizing the root cause of risks from networks between risk factors derived through SNA between risk factors enables more optimized and efficient risk management. This study is the first to apply SNA analysis techniques in relation to risk management response, and the results of this study are significant in that it not only optimizes the sequence of risk management for major risks in relation to risk management in IT projects but also presents a new risk analysis technique for risk control.