• Journal of Korea Society of Industrial Information Systems
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• v.21 no.4
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• pp.67-78
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• 2016

Recently many countries around the world are actively promoting smart city projects to address various urban problems such as traffic congestion, housing shortage, and energy scarcity. Due to development of the Internet of Things (IoT), the development of a smart city with sustainability, convenience, and environment-friendliness was enabled through the effective control and reuse of urban resources. The purpose of this study is to analyze the technical trends of IoT and present a development plan for smart city which is one of the applications of the IoT. To this end, the news articles of the Electronic Times between 2013 and 2015were analyzed using the text mining technique and smart city development cases of other countries were investigated. The analysis results revealed the close relationships of big data, cloud, platforms, and sensors with smart city. For the successful development of a smart city, first, all the interested parties in the city must work together to create new values throughout the entire process of value chain. Second, they must utilize big data and disclose public data more actively than they are doing now. This study has made academic contribution in that it has presented a big data analysis method and stimulated follow-up studies. For the practical contribution, the results of this study provided useful data for the policy making of local governments and administrative agencies for smart city development. This study may have limitations in the incorporation of the total trends because only the news articles of the Electronic Times were selected to analyze the technical trends of the IoT.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.806-816
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• 2021

This study aims to describe the reporting patterns of articles on the Emergency Grant for all citizens(EGAC) and compare the reporting attitudes by newspaper companies. The main results are as follows: First, conservative newspapers reported more than four times as much coverage of EGAC as liberal newspapers. Newspaper articles reported during the week of the National Assembly Election Day accounted for about a quarter of the total, and 79.1% of the articles were reported in the political realm of newspapers, and only 2.8% in the social realm. Second, a conservative newspaper reported a critical attitude toward EGAC at 52.6% and favorable articles at 5.3%. On the other hand, in a liberal newspaper, critical articles were 17.1% and favorable articles were 37.1%. The inefficiency of selectivism was reported as the basis for the argument in favor, and concerns about the burden of deterioration in the financial soundness of the opponents were reported the most. Politicians are the most cited sources of information in articles. Finally, in prior to policymaking, the proportion of the media in favor of and against the news was similar, and the proportion of articles with a neutral attitude accounted for more than half. And in the specific method discussion stage, the articles in favor of the article exceeded the proportion of articles on the opposite side.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.26-37
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• 2021

This study conducted a big data analysis on news to identify the agenda of media literacy, which has been socially discussed, and on which relevant policy directions will be proposed. To this end 1,336 articles from January 1, 2019 to September 30, 2020 were collected and a topic modeling analysis was conducted according to four periods. Five topics for each period were derived through the analysis, and implications based on the results are as follows. First, the government should implement a nation-level systematic approach to media literacy education according to life cycle stages to generate economic and cultural value. Second, local communities and schools should provide systematic support and education guidance activities to ensure a sustainable ecosystem for media literacy and prevent an educational gap and loss in learning. Third, efforts should be made in various aspects to minimize the side effects resulting from constantly providing media literacy education; furthermore a culture of desirable media application should be established. Finally, a research environment for scientific research on media literacy, active exchange of experience and value obtained in the field, and long-term accumulation of research results should be encouraged to develop a robust knowledge exchange culture.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

• Journal of Korean Home Economics Education Association
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• v.22 no.4
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• pp.1-13
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• 2010

The purpose of this study was to examine how the basic directions proposed in the Dietary Education Support Act were reflected in the dietary section of home economics textbooks for middle schools. The eleven different kinds of the 2007 revised textbooks were considered in the study. It was found that all of the textbooks considered reflected well in general the basic directions in the Dietary Support Act - formation of healthy dietary habits, promotion of dietary activities, practice of green dietary, preservation of traditional dietary, utilization of local food products, etc. in terms of their organization and description. However, it was also revealed that there were great differences among them in their treatment of visual materials like figures, photos, graphs, etc., news articles, and interesting anecdotal stories.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.55-63
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• 2017

One of the purposes of Information Technology (IT) is to support human response to natural and social problems such as natural disasters and spread of disease, and to improve the quality of human life. Recent climate change has happened worldwide, natural disasters threaten the quality of life, and human safety is no longer guaranteed. IT must be able to support tasks related to disaster response, and more importantly, it should be used to predict and minimize future damage. In South Korea, the data related to the damage is checked out by each local government and then federal government aggregates it. This data is included in disaster reports that the federal government discloses by disaster case, but it is difficult to obtain raw data of the damage even for research purposes. In order to obtain data, information extraction may be applied to disaster reports. In the field of information extraction, most of the extraction targets are web documents, commercial reports, SNS text, and so on. There is little research on information extraction for government disaster reports. They are mostly text, but the structure of each sentence is very different from that of news articles and commercial reports. The features of the government disaster report should be carefully considered. In this paper, information extraction method for South Korea government reports in the word format is presented. This method is based on patterns and dictionaries and provides some additional ideas for tokenizing the damage representation of the text. The experiment result is F1 score of 80.2 on the test set. This is close to cutting-edge information extraction performance before applying the recent deep learning algorithms.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.549-555
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• 2016

This paper tries to find the implications applied to art institutions of Korea by analyzing what the content and consequences of services of the Cleveland Museum of Art provided after the Internet of Things adoption in the theoretical perspectives strengthening service marketing through the Internet of Things increases visits and participation in the museum. For analysis, journal articles, statistics, and government press releases, news articles, web pages, web page articles are collected. The results are first, the application of digital and social media is positive in visit to the museum and monetization. Second, the introduction of the Internet of Things will enhance the museum's 'Education', 'Accessibility', 'Communications' services, as well as significantly increase on and offline participation by activating experience. Third, technical support from related companies with the support of local government funds is essential to build the system. Consequently, in order to enable the participation of the spectators in the galleries it is proposed aggressive adoption of such digital technology in domestic barren market of Internet of Things.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2005.11a
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• pp.73-77
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• 2005

To design senior housing that support residents' health is one of the comtemporary issues in Korea. As elderly people became more healthful and reach, people became interested in the health and health promotion. This trend encouraged this research study. The objectives of this study are: to analyze the middle aged people's opinions and behaviors related to health issues, and to suggest design considerations for senior housing. The survey used questionnaire from 476 residents living in Seoul and Gyeong-Gi area. The analysis used descriptive statistics, one-way anova and t-test. Primary findings are as follows: (1) Most of the respondents considered that their health state is 'good' and mental health is more important than physical health. (2) Many people exercise regularly for the promotion of health at a gym. (3) Results show that social relationship effect on health, and dietary life and walking medical examination account highly. (4) As the respondents are higher income and education level, the health-related behavior is more actively. Moreover the respondents who are women feel a great interest about health issues. These results suggest directions for planning of the senior housing. (1) Planning the space for the health-promoting behavior in the house or support a private gym-not a local facilities-. (2) Service for the information related health issues - medical examination, news of the health issues (3) Support the maintenance a good - social relationship (4) Consideration the space with health-related behavior like walking and dietary-life. The senior housing can reflect the health-related opinions and support health-related behavior of the elderly people.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.1
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• pp.41-50
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• 2024

Korea is facing a significant problem with historically low fertility rates, which is becoming a major social issue affecting the economy, labor force, and national security. This study analyzes the factors contributing to the regional gap in fertility rates and derives policy implications. The government and local authorities are implementing a range of policies to address the issue of low fertility. To establish an effective strategy, it is essential to identify the primary factors that contribute to regional disparities. This study identifies these factors and explores policy implications through machine learning and explainable artificial intelligence. The study also examines the influence of media and public opinion on childbirth in Korea by incorporating news and online community sentiment, as well as sentiment fear indices, as independent variables. To establish the relationship between regional fertility rates and factors, the study employs four machine learning models: multiple linear regression, XGBoost, Random Forest, and Support Vector Regression. Support Vector Regression, XGBoost, and Random Forest significantly outperform linear regression, highlighting the importance of machine learning models in explaining non-linear relationships with numerous variables. A factor analysis using SHAP is then conducted. The unemployment rate, Regional Gross Domestic Product per Capita, Women's Participation in Economic Activities, Number of Crimes Committed, Average Age of First Marriage, and Private Education Expenses significantly impact regional fertility rates. However, the degree of impact of the factors affecting fertility may vary by region, suggesting the need for policies tailored to the characteristics of each region, not just an overall ranking of factors.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.4
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• pp.299-307
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• 2024

Fishing villages, which are the focus of this study, are interested in fishing tourism for creating a new income base and sustaining fishing communities. This is because the extraordinary nature of the fishing village space creates new values in line with the function of tourism, however, the related policies are less than adequate compared to the importance of fishing village tourism. Therefore, this study aims to analyze the interest of Korean society in fishing village tourism the manner in which this issue has changed over time. Using the news analysis system, BigKinds, we systematically collected and analyzed articles related to fishing village tourism reported in the domestic media. The results showed that social interest in fishing village tourism and government policy support had increased over time, suggesting that fishing village tourism was an important strategy that could revitalize local economies and prevent the disappearance of fishing villages.