• The Journal of the Convergence on Culture Technology
• /
• v.8 no.5
• /
• pp.729-734
• /
• 2022

Various studies using accident cases are being conducted to identify the causes of accidents in the construction industry, but studies on the differences between public and private construction are insignificant. In this study, web scraping and text mining technologies were applied to analyze the causes of accidents by order type. Through statistical analysis and word cloud analysis of more than 10,000 structured and unstructured data collected, it was confirmed that there was a difference in the types and causes of accidents in public and private construction. In addition, it can contribute to the establishment of safety management measures in the future by identifying the correlation between major accident causes.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.20 no.2
• /
• pp.57-72
• /
• 2018

In order to extract meaningful information from the excellent farming settlement cases of young farmers published by KNCAF, we studied the key words with text mining and created a word cloud for visualization. First, in the text mining results for the entire sample, the words 'CEO', 'corporate executive', 'think', 'self', 'start', 'mind', and 'effort' are the words with high frequency among the top 50 core words. Their ability to think, judge and push ahead with themselves is a result of showing that they have ability of to be managers or managers. And it is a expression of how they manages to achieve their dream without giving up their dream. The high frequency of words such as "father" and "parent" is due to the high ratio of parents' cooperation and succession. Also 'KNCAF', 'university', 'graduation' and 'study' are the results of their high educational awareness, and 'organic farming' and 'eco-friendly' are the result of the interest in eco-friendly agriculture. In addition, words related to the 6th industry such as 'sales' and 'experience' represent their efforts to revitalize farming and fishing villages. Meanwhile, 'internet', 'blog', 'online', 'SNS', 'ICT', 'composite' and 'smart' were not included in the top 50. However, the fact that these words were extracted without omission shows that young farmers are increasingly interested in the scientificization and high-tech of agriculture and fisheries Next, as a result of grouping the top 50 key words by crop, the words 'facilities' in livestock, vegetables and aquatic crops, the words 'equipment' and 'machine' in food crops were extracted as main words. 'Eco-friendly' and 'organic' appeared in vegetable crops and food crops, and 'organic' appeared in fruit crops. The 'worm' of eco-friendly farming method appeared in the food crops, and the 'certification', which means excellent agricultural and marine products, appeared only in the fishery crops. 'Production', which is related to '6th industry', appeared in all crops, 'processing' and 'distribution' appeared in the fruit crops, and 'experience' appeared in the vegetable crops, food crops and fruit crops. To visualize the extracted words by text mining, we created a word cloud with the entire samples and each crop sample. As a result, we were able to judge the meaning of excellent practices, which are unstructured text, by character size.

• Journal of Society of Preventive Korean Medicine
• /
• v.26 no.2
• /
• pp.25-35
• /
• 2022

Objectives : This study aims to analyze the patents filed in the clinical diagnosis sector where technologies have been actively developed since the advent of the 4th industrial revolution. Methods : The analysis has been conducted in two ways - the period from 2016 to 2021 and the time points before and after COVID-19 - by visualizing based on the word cloud method. Results : Over two thirds of patents has been filed in the A61B sector (71.8%) and cure, sensor, self diagnosis, control, and breakdown have been observed in the period above. During the overall period (2016~2021), 'ultrasound'(7.5%), 'image'(5.1%), 'skin'(4.0%), 'treatment'(3.4%), and 'artificial intelligence(2.5%)' were the frequently patent applications technologies. In addition, 'ultrasound'(6.2%), 'image'(5.5%), 'skin'(4.0%), 'treatment' (3.7%), and 'portable'(1.7%) appeared most frequently before COVID-19 whereas 'ultrasound(5.5%)', 'artificial intelligence(4.2%)', 'diagnostic device'(1.9%), 'dimentia'(1.6%), and 'diagnostic kit'(1.4%) emerged the most after COVID-19. Conclusion : This study is meaningful in that it showed the technological development trend in the digital diagnosis sector and it was found that the Korean medicine field should contribute to this field more actively in the future.

• Proceedings of the National Institute of Ecology of the Republic of Korea
• /
• v.4 no.1
• /
• pp.43-48
• /
• 2023

This study analyzed research trends in the field of ecological research. Data were collected based on a keyword search of the SCI, SSCI, and A&HCI databases from January 2002 to September 2022. The seven keywords, including biodiversity, ecology, ecotourism, species, climate change, ecosystem, restoration, wildlife, were recommended by ecological research experts. Word clouds were created for each of the searched keywords, and topic map analysis was performed. Topic map analysis using biodiversity, climate change, ecology, ecosystem, and restoration each generated 10 topics; topic maps analysis using the ecotourism keyword generated 5 topics; and topic map analysis using the wildlife keyword generated 4 topics. Each topic contained six keywords.

• Journal of Fashion Business
• /
• v.26 no.6
• /
• pp.1-13
• /
• 2022

The purpose of this study was to find out the type of fashion codes hip-hop fashion has in contemporary Chinese fashion, and the frequency and characteristics of each fashion code. Text mining, which is the most basic analysis method in big data analyticswas used rather than traditional design element analysis. Specific results were as follows. First, hip-hop initially entered China in the late 1970s. The most historical turning point was the American film "Breakin". Second, frequency and word cloud analysis results showed that the "national tide" fashion code was the most notable code. Third, through word embedding analysis, fashion codes were divided into types of "original hip-hop codes", "trendy hip-hop codes", and "hip-hop codes grafted with traditional Chinese culture".

• Genomics & Informatics
• /
• v.17 no.3
• /
• pp.25.1-25.6
• /
• 2019

Genomics & Informatics (NLM title abbreviation: Genomics Inform) is the official journal of the Korea Genome Organization. Herein, we conduct a statistical analysis of the publications of Genomics & Informatics over the 16 years since its inception, with a particular focus on issues relating to article categories, word clouds, and the most-studied genes, drawing on recent reviews of the use of word frequencies in journal articles. Trends in the studies published in Genomics & Informatics are discussed both individually and collectively.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.8
• /
• pp.91-101
• /
• 2021

This paper intends to draw implications for preparing for Post-Corona in the health field and policy fields as the global pandemic is experienced due to COVID-19. The purpose of this study is to analyze the news and trends of media companies through temporal analysis of the three infectious diseases, SARS-CoV, MERS-CoV, and SARS-CoV-2 (COVID-19), in which the domestic infectious disease preventive system was active throughout the first year of the outbreak. To this end, by using the news analysis program of the Korea Press Foundation 'Big Kinds', the number of news articles per year was digitized based on the period when each infectious disease had an impact on Korea, and major trends were implemented and analyzed in a word cloud. As a result of the analysis, the number of articles related to infectious diseases peaked when the World Health Organization (WHO) declared a warning and (suspicious) confirmed cases occurred. According to keyword and word cloud analysis, 'infectious disease outbreak and major epidemic areas', 'prevention authorities', and 'disease information and confirmed patient information' were found to be the main common features, and differences were derived from the three infectious diseases. In addition, the current status of the infodemic was identified by performing word cloud analysis on information in uncertainty. The results of this study are significant in that they were able to derive the roles of the health authorities and the media that should be preceded in the event of a new disease epidemic through previously experienced infectious diseases, and areas to be rearranged.

• Journal of Korea Society of Industrial Information Systems
• /
• v.20 no.2
• /
• pp.113-124
• /
• 2015

Unlike structured data which are gathered and saved in a predefined structure, unstructured text data which are mostly written in natural language have larger applications recently due to the emergence of web 2.0. Text mining is one of the most important big data analysis techniques that extracts meaningful information in the text because it has not only increased in the amount of text data but also human being's emotion is expressed directly. In this study, we used R program, an open source software for statistical analysis, and studied algorithm implementation to conduct analyses (such as Frequency Analysis, Cluster Analysis, Word Cloud, Social Network Analysis). Especially, to focus on our research scope, we used keyword extract method based on a Data Dictionary. By applying in real cases, we could find that R is very useful as a statistical analysis software working on variety of OS and with other languages interface.

• Journal of Korean Society for Quality Management
• /
• v.49 no.4
• /
• pp.551-567
• /
• 2021

Purpose: The purpose of this paper is to present implications by analyzing research trends on smart factories by text analysis and visual analysis(Comprehensive/ Fields / Years-based) which are big data analyses, by collecting data based on previous studies on smart factories. Methods: For the collection of analysis data, deep learning was used in the integrated search on the Academic Research Information Service (www.riss.kr) to search for "SMART FACTORY" and "Smart Factory" as search terms, and the titles and Korean abstracts were scrapped out of the extracted paper and they are organize into EXCEL. For the final step, 739 papers derived were analyzed using the Rx64 4.0.2 program and Rstudio using text mining, one of the big data analysis techniques, and Word Cloud for visualization. Results: The results of this study are as follows; Smart factory research slowed down from 2005 to 2014, but until 2019, research increased rapidly. According to the analysis by fields, smart factories were studied in the order of engineering, social science, and complex science. There were many 'engineering' fields in the early stages of smart factories, and research was expanded to 'social science'. In particular, since 2015, it has been studied in various disciplines such as 'complex studies'. Overall, in keyword analysis, the keywords such as 'technology', 'data', and 'analysis' are most likely to appear, and it was analyzed that there were some differences by fields and years. Conclusion: Government support and expert support for smart factories should be activated, and researches on technology-based strategies are needed. In the future, it is necessary to take various approaches to smart factories. If researches are conducted in consideration of the environment or energy, it is judged that bigger implications can be presented.

• Journal of Digital Convergence
• /
• v.20 no.5
• /
• pp.173-178
• /
• 2022

With the development of information technology, the popularization of 5G and cloud computing has accelerated the circulation and digital transformation of information. In the network information society where information is rapidly increasing, it is very important to have the ability to manage and collect the required information. In particular, the information storage and management functions of cloud services are widely used among young people. This research takes the social factors of accepting cloud services as the breakthrough point, and takes young consumers aged 20-30 as the survey object, and designs a research model according to the development of cloud computing technology. The findings verify the influence of social factors on cloud service acceptance and 20-30-year-old consumers' intention to use cloud services. The partial and complete mediating effects of perceived ease of use were verified from the influence relationship between social factors and exploitation intention. Finally, this study provides inspiration for the development direction of cloud computing technology through empirical analysis.