• Journal of Digital Convergence
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• v.19 no.12
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• pp.29-42
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• 2021

As the low fertility intensifies in Korea, this study investigated fundamental differences between the government's low fertility policy and public perception of it. To this end, we selected four times 'Aging Society and Population Policy' documents and news comments for two weeks immediately after announcement of the third and fourth Policy as analysis targets. Then we conducted word frequency analysis, co-occurrence analysis and CONCOR analysis. As a result of analyses, first, direct childcare support during the first and second periods, and a social structural approach during third and fourth periods were noticeable. Second, it was revealed that both policies and comments aim for the work-family compatibility in 'parenting'. Lastly it was showed public interest in environment of raising children and the critical mind to effectiveness of the policy. This study is meaningful in that it confirmed the public perception using big data analysis, and it will help improve the direction for the future low fertility policy.

• Informatization Policy
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• v.25 no.4
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• pp.37-64
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• 2018

This study aims to forecast the future of the Korean society via a big data analysis. Based upon two sets of database - a collection of 46,000,000 news on 127 media in Naver Portal operated by Naver Corporation and a collection of 70,000 academic papers of social sciences registered in KCI (Korea Citation Index of National Research Foundation) between 2005-2017, 40 most frequently occurring keywords were selected. Next, their temporal variations were traced and compared in terms of number and pattern of frequencies. In addition, core issues of the future were identified through keyword network analysis. In the case of the media news database, such issues as economy, polity or technology turned out to be the top ranked ones. As to the academic paper database, however, top ranking issues are those of feeling, working or living. Referring to the system and life-world conceptual framework suggested by $J{\ddot{u}}rgen$ Habermas, public interest of the future inclines to the matter of 'system' while professional interest of the future leans to that of 'life-world.' Given the disparity of future interest, a 'mismatch paradigm' is proposed as an alternative to social forecasting, which can substitute the existing paradigms based on the ideas of deficiency or deprivation.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.121-129
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• 2021

In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

• Smart Media Journal
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• v.9 no.4
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• pp.66-72
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• 2020

As the online education market expands, educational contents with various presentation methods are being developed and released. In addition, it is imperative to develop content that reflects the usability and user environment of users who use this educational content. However, for qualitative growth of contents that will support quantitative expansion of markets, existing model analysis methods are urgently needed at a time when development direction of newly developed contents is secured. In this process of content development, a typical model for setting development goals is needed, as the rules of the prototype affect the entire development process and the final development outcome. It can also provide a positive benefit that screens the issue of performance dualization between processes due to the absence of communication between a single entity or between a number of entities. In the case of AR-based educational content which is effective to secure data necessary for development by securing samples of similar categories because there are not enough ready-made samples released. Therefore, a big data statistical analysis service is needed that can easily collect data and make decisions using big data. In this paper, we would like to design analysis services that enable the selection and detection of intuitive multidimensional factors and attributes, and propose big data-based statistical analysis services that can assist cooperative activities within an organization or among many companies.

• 한국노년학
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• v.41 no.4
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• pp.505-525
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• 2021

Purpose. The purpose of this study is to examine how the phrase "old person" are expressed and used in the online sphere. Based on the theoretical concept of stigma, this study investigates the images and attitudes in society toward the elderly, and the characteristics of hate speech aimed at the elderly. Method. This study conducted text mining based on social big data using anonymous conversations. Results. It was confirmed that the elderly images shared online were generally negative. The attitudes expressed toward them also tended to be negative due to the negative images that are propagated of the elderly. The hate speech relating to the elderly, in usages such as 'Teul-ttag' and 'Kon-dae', were mainly identified in comments that negatively evaluate the elderly, and these expressions demonstrate the depth of hate and discrimination towards the elderly who are considered burdensome by young people. Interestingly, the hateful expressions towards the elderly were found more with regard to issues related to politics and economics and not just any content about the elderly. Conclusions. This study discussed the ways and means to enhance inter-generational understanding and solidity.

• Korean Journal of Heritage: History & Science
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• v.56 no.1
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• pp.162-180
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• 2023

The World Heritage Committee decided to make "cultural landscapes" a world heritage category in the 16th Session of the UNESCO General Conference. The decision was made from a recognition of the importance of interactions between human beings and the natural environment or between cultural heritage and natural heritage. Many countries have created policies and institutions to protect their own cultural landscapes along with the changing times. Korea, however, has not obviously defined the concepts and categories of its cultural landscapes, but manages policies and institutions based on the concept of a scenic spot, which has some similar meanings. In addition, it even borrows the "list of landscape adjectives," one of the representative methods for managing landscapes, from foreign countries. With this background, this paper suggested how to define cultural landscapes according to the global development flow. It created a list of cultural landscape adjectives by gathering the adjectives that can properly express local cultural landscapes in Korea. In particular, it collected 4,556 articles from a local newspaper by focusing on the case of Shinan-gun, Jeollanam-do, and analyzed key words and adjectives included in them by using big data analysis. The results suggested by this paper, such as the "classification table of cultural landscape types," "list of cultural landscape adjectives" and "network map of nouns/adjectives" can be applied to research on other localities, and furthermore, used as basic data for finding and protecting the characteristics of local cultural landscapes in Korea.

• Convergence Security Journal
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• v.22 no.5
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• pp.69-80
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• 2022

Now that climate change and food resource security are becoming issues around the world, smart farms are emerging as an alternative to solve them. In addition, changes in the production environment in the primary industry are a major concern for people engaged in all primary industries (agriculture, livestock, fishery), and the resulting food shortage problem is an important problem that we all need to solve. In order to solve this problem, in the primary industry, efforts are made to solve the food shortage problem through productivity improvement by introducing smart farms using the 4th industrial revolution such as ICT and BT and IoT big data and artificial intelligence technologies. This is done through the public and private sectors.This paper intends to consider the minimum requirements for the smart farm data collection system for the development and utilization of smart farms, the establishment of a sustainable agricultural management system, the sequential system construction method, and the purposeful, efficient and usable data collection system. In particular, we analyze and improve the problems of the data collection system for building a Korean smart farm standard model, which is facing limitations, based on in-depth investigations in the field of livestock and livestock (pig farming) and analysis of various cases, to establish an efficient and usable big data collection system. The goal is to propose a method for collecting big data.

• Convergence Security Journal
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• v.22 no.4
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• pp.85-97
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• 2022

With the development of big data technology, data is rapidly entering a hyperconnected intelligent society that accelerates innovative growth in all industries. The convergence industry, which holds and utilizes various high-quality data, is becoming a new growth engine, and big data is fused to various traditional industries. In particular, in the medical field, structured data such as electronic medical record data and unstructured medical data such as CT and MRI are used together to increase the accuracy of disease prediction and diagnosis. Currently, the importance and size of unstructured data are increasing day by day in the medical industry, but conventional data security technologies and policies are structured data-oriented, and considerations for the security and utilization of unstructured data are insufficient. In order for medical treatment using big data to be activated in the future, data diversity and security must be internalized and organically linked at the stage of data construction, distribution, and utilization. In this paper, the current status of domestic and foreign data security systems and technologies is analyzed. After that, it is proposed to add unstructured data-centered de-identification technology to the guidelines for unstructured data and technology application cases in the industry so that unstructured data can be actively used in the medical field, and to establish standards for judging personal information for unstructured data. Furthermore, an object feature-based identification ID that can be used for unstructured data without infringing on personal information is proposed.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.1-20
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• 2022

As the global business environment is rapidly changing due to the 4th industrial revolution, new jobs that did not exist before are emerging. Among them, the job that companies are most interested in is 'Data Scientist'. As information and communication technologies take up most of our lives, data on not only online activities but also offline activities are stored in computers every hour to generate big data. Companies put a lot of effort into discovering new opportunities from such big data. The new job that emerged along with the efforts of these companies is data scientist. The demand for data scientist, a promising job that leads the big data era, is constantly increasing, but its supply is not still enough. Although data analysis technologies and tools that anyone can easily use are introduced, companies still have great difficulty in finding proper experts. One of the main reasons that makes the data scientist's shortage problem serious is the lack of understanding of the data scientist's job. Therefore, in this study, we explore the job competencies of a data scientist by qualitatively analyzing the actual job posting information of the company. This study finds that data scientists need not only the technical and system skills required of software engineers and system analysts in the past, but also business-related and interpersonal skills required of business consultants and project managers. The results of this study are expected to provide basic guidelines to people who are interested in the data scientist profession and to companies that want to hire data scientists.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.429-450
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• 2023

The purpose of this study is to examine recent trends and intellectual structures in research related to open data. To achieve this, the study conducted a search for the keyword "open data" in Scopus and collected a total of 6,543 papers from 1999 to 2023. After data preprocessing, the study focused on the author keywords of 5,589 papers to perform network analysis and derive centrality in the field of open data research and linked open data research. As a result, the study found that "big data" exhibited the highest centrality in research related to open data. The research in this area mainly focuses on the utilization of open data as a concept of public data, studies on the application of open data in analysis related to big data as an associated concept, and research on topics related to the use of open data, such as the reproduction, utilization, and access of open data. In linked open data research, both triadic centrality and closeness centrality showed that "the semantic web" had the highest centrality. Moreover, it was observed that research emphasizing data linkage and relationship formation, rather than public data policies, was more prevalent in this field.