• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.655-662
• /
• 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 Industrial Convergence
• /
• v.21 no.10
• /
• pp.21-28
• /
• 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.

• The Korean Journal of Applied Statistics
• /
• v.36 no.5
• /
• pp.489-499
• /
• 2023

As sharing of analyst reports became widely available, reports generated by analysts have become a useful tool to reduce difference in financial information between market participants. The quantitative information of analyst reports has been used in many ways to predict stock returns. However, there are relatively few domestic studies on the prediction power of text information in analyst reports to predict stock returns. We test stock return predictability of text in analyst reports by creating variables representing the TONE from the text. To overcome the limitation of the linear-model-assumption-based approach, we use the random-forest-based F-test.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.6
• /
• pp.935-940
• /
• 2023

Most text data collected through web scraping for artificial intelligence and big data analysis is generally large and unstructured, so a purification process is required for big data analysis. The process becomes structured data that can be analyzed through a heuristic pre-processing refining step and a post-processing machine refining step. Therefore, in this study, in the post-processing machine refining process, the Korean dictionary and the stopword dictionary are used to extract vocabularies for frequency analysis for word cloud analysis. In this process, "user-defined stopwords" are used to efficiently remove stopwords that were not removed. We propose a methodology for applying the "thesaurus" and examine the pros and cons of the proposed refining method through a case analysis using the "user-defined stop word thesaurus" technique proposed to complement the problems of the existing "stop word dictionary" method with R's word cloud technique. We present comparative verification and suggest the effectiveness of practical application of the proposed methodology.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.27 no.5
• /
• pp.49-56
• /
• 2023

This study proposed a damage location estimation method for automated image-based port infrastructure inspection. Memory efficiency was improved by calculating the homography matrix using feature detection technology and outlier removal technology, without going through the 3D modeling process and storing only damage information. To develop an algorithm specialized for port infrastructure, the algorithm was optimized through ground-truth coordinate pairs created using images of port infrastructure. The location errors obtained by applying this to the sample and concrete wall were (X: 6.5cm, Y: 1.3cm) and (X: 12.7cm, Y: 6.4cm), respectively. In addition, by applying the algorithm to the concrete wall and displaying it in the form of an exterior damage map, the possibility of field application was demonstrated.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.6
• /
• pp.13-22
• /
• 2024

There is a need for and positive aspects of article-based advertising, but as exaggerated and disguised information is delivered due to some indiscriminate 'article-based advertisements', readers have difficulty distinguishing between general articles and article-based advertisements, leading to a lot of misinterpretation and confusion of information. is doing Since readers will continue to acquire new information and apply this information at the right time and place to bring a lot of value, it is judged to be even more important to distinguish between accurate general articles and article-like advertisements. Therefore, as differentiated information between general articles and article-like advertisements is needed, as part of this, for readers who have difficulty identifying accurate information due to such indiscriminate article-like advertisements in Internet newspapers, this paper introduces IT and AI technologies. We attempted to present a method that can be solved in terms of a system that incorporates, and this method was designed to extract articleable advertisements using a knowledge-based natural language processing method that finds and refines advertising keywords and deep learning technology.

• Dementia and Neurocognitive Disorders
• /
• v.22 no.2
• /
• pp.49-60
• /
• 2023

Background and Purpose: The National Responsibility Policy for Dementia Care was implemented in September 2017 in Korea. This study aimed to compare dementia incidence in Seoul and Gangwon-do before and after the implementation of this policy. Methods: We extracted insurance claim data from the Korean Health Insurance Review and Assessment Service for people diagnosed with diabetes, hypertension, or dyslipidemia for the first time in Seoul and Gangwon-do, Korea. We defined two enrollment groups based on the policy implementation date: 1) January 1, 2015 to December 31, 2016 (Index 1, pre-implementation), and 2) January 1, 2017 to December 31, 2018 (Index 2, post-implementation). Each group was followed up for 1 year from the time of enrollment. Then, we calculated hazard ratios to compare the incidence of dementia between the two groups, and between Seoul and Gangwon-do. Results: In Seoul, the incidence of dementia was significantly lower in Index 2 than in Index 1 (hazard ratio [HR], 0.926; 95% confidence interval [CI], 0.875-0.979). However, the incidence rate did not differ between the 2 groups (HR, 1.113; 95% CI, 0.966-1.281) in Gangwon-do. In Index 1, the incidence of dementia did not differ between Seoul and Gangwon-do (HR, 1.043; 95% CI, 0.941-1.156), but in Index 2, was significantly higher in Gangwon-do than in Seoul (HR, 1.240; 95% CI, 1.109-1.386). Conclusions: After implementing the National Responsibility Policy for Dementia Care, the dementia incidence rate decreased significantly in Seoul, consistent with other studies, but not in Gangwon-do.

• Journal of Digital Convergence
• /
• v.17 no.10
• /
• pp.49-58
• /
• 2019

In the era of the 4th industrial revolution, the development of information technology brought various benefits, but it also increased social interest in privacy issues. As the possibility of personal privacy violation by big data increases, academic discussion about privacy management has begun to be active. While the traditional view of privacy has been defined at various levels as the basic human rights, most of the recent research trends are mainly concerned only with the information privacy of online privacy protection. This limited discussion can distort the theoretical concept and the actual perception, making the academic and social consensus of the concept of privacy more difficult. In this study, we analyze the privacy concept that is exposed on the internet based on 12,000 news data of the portal site for the past one year and compare the difference between the theoretical concept and the socially accepted concept. This empirical approach is expected to provide an understanding of the changing concept of privacy and a research direction for the conceptualization of privacy for current situations.

• Journal of the Korea Convergence Society
• /
• v.12 no.4
• /
• pp.207-216
• /
• 2021

Recently, there is increasing interest in attracting local tourist in the city to revitalize the local economy. For this purpose, customized tourism strategies based on the analysis of travel routes and consumption patterns are becoming important. However, existing studies either focused on limited mainstream tourist analysis or lacked analysis of tourists' behavior-based data perspectives. Therefore, this study aims to present a big data-based tourism strategy that provides customized information by analyzing the demand of individual travelers in details based on mobile service data and card expenditure data generated by the travelers in Yongin city. By tracing those data, this study visualized the tourists' itinerary and their expenditure patterns. The analysis of data from July 2017 to June 2018 shows that men tend to consume in various areas compared to women. It also shows consumption areas for people in their 30s and 40s are similar, whereas those in their 20s do not vary. Using the big data based on Geographic Information system, this study provides strategic insights to administrative personnel who are in charge of tour policy.

• Convergence Security Journal
• /
• v.20 no.4
• /
• pp.27-34
• /
• 2020

Recently, the fourth industrial revolution technology has not only changed everyday life greatly through technological development, but has also become a major keyword in the establishment of defense policy. In particular, Internet of Things, cloud, big data, mobile and cybersecurity technologies, called ICBMS, were selected as core leading technologies in defense information policy along with artificial intelligence. Amid the growing importance of the fourth industrial revolution technology, research is being carried out to develop the C4I system, which is currently operated separately by the Joint Chiefs of Staff and each military, including the KJCCS, ATCIS, KNCCS and AFCCS, into an integrated system in preparation for future warfare. This is to solve the problem of reduced interoperability for joint operations, such as information exchange, by operating the C4I system for each domain. In addition, systems such as the establishment of an integrated C4I system and the U.S. military's Risk Management Framework (RMF) are essential for efficient control and safe operation of weapons systems as they are being developed into super-connected and super-intelligent systems. Therefore, in this paper, the intelligent cyber threat detection, management of users' access to information, and intelligent management and visualization of cyber threat are presented in the future C4I system based on big data/cloud.