• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.9
• /
• pp.6411-6418
• /
• 2015

To respond the climate change and environmental pollution, the studies on renewable energy policies are increasing. The renewable energy is a new growth engine technology represented by the green industry and green technology. At present, the investments for the renewable energy supply and technology development projects of three main strategy sectors such as sunlight, wind power and hydrogen fuel cell are implemented in our country, while they are still in the early stage, accordingly reducing those uncertainty for the research direction and investment fields is the most urgent issue among others. Thus, this study applied text mining method and multinominal topic model among the big data analysis methods on our country's newspaper articles concerning the renewable energy over the last 10 years, and then analyzed the core issues and global research trend, forecasting the renewable energy fields with the growth potential. It is predicted that these results of the study based on information and communication technology will be actively applied on the renewable energy fields.

• Journal of Korea Society of Industrial Information Systems
• /
• v.23 no.3
• /
• pp.87-95
• /
• 2018

Recently, with the technological development of artificial intelligence, related market is expanding rapidly. In the artificial intelligence technology field, which is still in the early stage but still expanding, it is important to reduce uncertainty about research direction and investment field. Therefore, this study examined technology trends using text mining and topic modeling among big data analysis methods and suggested trends of core technology and future growth potential. We hope that the results of this study will provide researchers with an understanding of artificial intelligence technology trends and new implications for future research directions.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.1
• /
• pp.231-238
• /
• 2021

In this paper, we suggest a method of analysis for daily food delivery & consumption trends through big data of the post-Covid-19 era. Through analysis of big data and the database system, four analyzed factors, excluding weather, was proved to have significant correlation with delivery sales for 'Baedarui Minjok' of a catering delivery application. The research found that KBS, MBC and SBS Media showed remarkable results in food delivery & consumption sales soaring up to about 60 percent increase on the day after the Covid-19 related new article was issued. In addition, it proved that mobile media and web surfing were the main factors in increasing sales of food delivery & consumption applications, suggesting that viral marketing and emotional analysis by crawling data from SNS used by Millennials might be an important factor in sales growth. It can contribute the companies in the economic recession era to survive by providing the method for analyzing the big data and increasing their sales.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.22 no.3
• /
• pp.49-61
• /
• 2020

This study analyzed the social media accounts and performed a Big Data analysis of Z-generation fashion using Textom Text Mining Techniques program and Ucinet Big Data analysis program. The research results are as follows: First, as a result of keyword analysis on 67.646 Z-generation fashion social media posts over the last 5 years, 220,211 keywords were extracted. Among them, 67 major keywords were selected based on the frequency of co-occurrence being greater than more than 250 times. As the top keywords appearing over 1000 times, were the most influential as the number of nodes connected to 'Z generation' (29595 times) are overwhelmingly, and was followed by 'millennials'(18536 times), 'fashion'(17836 times), and 'generation'(13055 times), 'brand'(8325 times) and 'trend'(7310 times) Second, as a result of the analysis of Network Degree Centrality between the key keywords for the Z-generation, the number of nodes connected to the "Z-generation" (29595 times) is overwhelmingly large. Next, many 'millennial'(18536 times), 'fashion'(17836 times), 'generation'(13055 times), 'brand'(8325 times), 'trend'(7310 times), etc. appear. These texts are considered to be important factors in exploring the reaction of social media to the Z-generation. Third, through the analysis of CONCOR, text with the structural equivalence between major keywords for Gen Z fashion was rearranged and clustered. In addition, four clusters were derived by grouping through network semantic network visualization. Group 1 is 54 texts, 'Diverse Characteristics of Z-Generation Fashion Consumers', Group 2 is 7 Texts, 'Z-Generation's teenagers Fashion Powers', Group 3 is 8 Texts, 'Z-Generation's Celebrity Fashions' Interest and Fashion', Group 4 named 'Gucci', the most popular luxury fashion of the Z-generation as one text.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.2
• /
• pp.435-442
• /
• 2017

Our anxiousness has risen for recent increase in unpredicatable disaster. Accordingly, for the future society's preventing measure in advance against current considerable disasters due to societal crisis, we need to prepare secure measure ahead. Hence, we need to recognize the significance of governmental role and the value of Big Data application as ICT developed country in order to manage social crisis all the time. This manuscript analyzes human anxiety from listed disasters and describes that our government seeks new way to utilize Big Data in public in order to visualize Big Data related issues and its significance and urgency. Also, it suggests domestic/international application trend of Big Data's public sector with new practical approach to Big Data. Then, it emphasizes e-Gov's role for its Big Data application and suggests policies implying governmental use of Big Data for social crisis management by case-studying disaster measures against unpredictable crisis.

• Journal of Industrial Convergence
• /
• v.17 no.2
• /
• pp.21-27
• /
• 2019

The Internet of things is the infrastructure that can communicate with each other by exchanging information by installing antennas that can communicate with all things in the world. The reason why the Internet of Things is the core of the Fourth Industrial Revolution is that data is collected through the Internet to be. Technology of things Internet and Trend of Things Internet IoT (Internet of Things) is a concept that enables internet connection and communication between devices equipped with various sensors. It is the core IT trend of lot, technology such as big data, mobile, cloud And to provide information for the development of the industrial environment through research on the importance of the Internet of things, the core of the Fourth Industrial Revolution and the processing and analysis techniques of Big Data. By providing various security measures and future technologies, This study was conducted to contribute to management.

• Korean Association of Arts Management
• /
• no.50
• /
• pp.5-31
• /
• 2019

The main purpose of this study was to use Deep Learning based Topic Modeling and Semantic Network Analysis to examine research trend of arts management-related papers in korea. For this purpose, research subjects such as 'The Journal of Cultural Policy', 'The Journal of Cultural Economics', 'The Journal of Culture Industry', 'The Journal of Arts Management', and 'The Journal of Human Content', which are the registered journal of the National Research Foundation of Korea directly or indirectly related to arts management field. From 1988 to 2017, a total of 2,110 domestic journals' signature, abstract, and keyword were analyzed. We tried Big Data analysis such as Topic Modeling and Semantic Network Analysis to examine changes in trends in arts management. The analysis program used open software R and standard statistical software SPSS. Based on the results of the analysis, the implications and limitations of the study and suggestions for future research were discussed. And the potential for development of convergent research such as Arts & Artificial Intelligence and Arts & Big Data.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.5
• /
• pp.207-214
• /
• 2020

Nowadays, the use of smart phones and various electronic devices is increasing, the Internet and SNS are activated, and we live in the flood of information. The amount of information has grown exponentially, making it difficult to look at a lot of information, and more and more people want to see only key keywords in a document, and the importance of research to extract topics that are the core of information is increasing. In addition, it is also an important issue to extract the topic and compare it with the past to infer the current trend. Topic modeling techniques can be used to extract topics from a large volume of documents, and these extracted topics can be used in various fields such as trend prediction and data analysis. In this paper, we inquire the topic of the three-year papers of 2016, 2017, and 2018 in the field of computing using the LDA algorithm, one of Probabilistic Topic Model Techniques, in order to analyze the rapidly changing trends and keep pace with the times. Then we analyze trends and flows of research.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.6
• /
• pp.287-294
• /
• 2022

The purpose of this study is to find out consumers' perceptions of "metaverse," a newly spotlighted technology, through big data analysis as a non-face-to-face society continues after the outbreak of COVID-19. This study conducted a big data analysis using text mining to analyze consumers' perceptions of metaverse before and after COVID-19. The top 30 keywords were extracted through word purification, and visualization was performed through network analysis and concor analysis between each keyword based on this. As a result of the analysis, it was confirmed that the non-face-to-face society continued and metaverse emerged as a trend. Previously, metaverse was focused on textual data such as SNS as a part of life logging, but after that, it began to pay attention to virtual reality space, creating many platforms and expanding industries. The limitation of this study is that since data was collected through the search frequency of portal sites, anonymity was guaranteed, so demographic characteristics were not reflected when data was collected.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.05a
• /
• pp.904-907
• /
• 2013

최근 정보통신기술이 하루가 다르게 발전함에 따라 하루에도 수많은 데이터가 흘러나오는 최근의 추세이다. 정형 데이터 뿐 아니라 비정형 데이터 분석까지 진행하는 최근의 추세에 맞춰 현 빅데이터 기술 동향을 분석한다. 빅데이터 시대를 맞아 기존의 데이터웨어하우스(DW)와 발전된 데이터웨어하우스(DW) 어플라이언스에 대해 분석하고 향후 발전 전망과 방향을 제시한다.