• Journal of Information Technology Services
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• v.18 no.2
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• pp.123-141
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• 2019

The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.981-993
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• 2018

Smart healthcare is convergence of ICT and healthcare services, and interdisciplinary research has been actively conducted in various fields. The objective of this study is to investigate trends of smart healthcare research using topic modeling and ego network analysis. Text analysis, frequency analysis, topic modeling, word cloud, and ego network analysis were conducted for the abstracts of 2,690 articles in Scopus from 2001 to April 2018. Topic Modeling analysis resulted in eight topics, Topics included "AI in healthcare", "Smart hospital", "Healthcare platform", "Blockchain in healthcare", "Smart health data", "Mobile healthcare", " Wellness care", "Cognitive healthcare". In order to examine the topic modeling results core deeply, we analyzed word cloud and ego network analysis for eight topics. This study aims to identify trends in smart healthcare research and suggest implications for establishing future research direction.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.11-19
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• 2021

The presidential inaugural address is a very useful means of presenting the national vision and conveying the president's political philosophy and policy direction to the people. For this reason, analyzing the address will help to understand the president him/herself and the presidential times. The address can be analyzed in various academic fields, but in this study, it was considered as only content and analyzed based on the network. It is widely used for word cloud analysis based on the frequency of words appearing in the address. If it is analyzed based on a network, it will be a useful method because it is possible to derive the context contained in the sentence. The entire network of the addresses of past presidents of the Republic of Korea was established and structural factors were presented. The president and political direction were derived by comparatively analyzing the key words derived from the network and the word cloud. The characteristics of the address were presented by comparing and analyzing key words and closeness centrality, which is a structural factor of the network, by constructing a network of each president's inaugural address. It is expected that the network-based analysis of past presidential inaugural addresses can ultimately be used as data for understanding and evaluating presidents.

• The Korean Journal of Emergency Medical Services
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• v.24 no.1
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• pp.85-92
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• 2020

Purpose: The purpose of this study was to analyze the English abstract key words found within the Korea Society of Emergency Medical Services journal using text mining techniques to determine the adherence of these terms with Medical Subject Headings (MeSH) and identify key word trends. Methods: We analyzed 212 papers that were published from 2012 to 2019. R software, web scraping, and frequency analysis of key words were conducted using R's basic and text mining packages. Additionally, the Word Clouds package was used for visualization. Results: The average number of key words used per study was 3.9. Word cloud visualization revealed that CPR was most prominent in the first half and emergency medical technician was most frequently used during the second half. There were a total of 542 (64.9%) words that exactly matched the MeSH listed words. A total of 293 (35%) key words did not match MeSH listed words. Conclusion: Researchers should obey submission rules. Further, journals should update their respective submission rules. MeSH key words that are frequently cited should be suggested for use.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.27-34
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• 2018

This study was conducted to identify the contents of major consulting needs of SMEs using Big Data and to suggest the efficiency of operation. The subjects of the study were counseling cases posted on the website of the Business Support Center of the Ministry of SMEs and Startups. To do this, from 2009 to March 2018, we crawled about 7,000 cases of counseling cases, followed by word cloud analysis centering on effective keyword. The main results were as follows: First, the frequency of counseling cases in each field was found in the order of establishment, management strategy, human resources, financial order. Second, in word cloud analysis, the most frequent keyword related to counseling demand were small businesses, exports, methods, procedures, registration and authentication. In this study, we obtained research results that we can improve the efficiency of the policy in real time from a new point of view by conducting big data analysis on public policy.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.3
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• pp.109-119
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• 2019

The purpose of this study is to examine fashion trends and the direction of the four fashion collections by analyzing the design key-words of the four major international fashion collections in 2018. The data of this study was collected by extracting the key-words from Marie Claire Korea in 2018, with the total of the collected data numbering 2,144. The data was analyzed by text mining using the R program and word-cloud, and a co-occurrence network analysis was conducted. The results of this study are as follows: First, the key-words of fashion collection designs in 2018 were fringe and ruffle detail, silk and denim fabric, vivid color, stripe and check pattern, pants suit item, and oversized silhouette, focusing on romanticism and sport. Second, seasonal characteristics of the fashion collections were pastel colors in S/S, primary and vivid colors in F/W. Details were embroidery and cutouts in S/S, patchwork and fringe in F/W. Third, the design trends of the four major fashion collections were presented in the Paris collection: stripes, check patterns, embroidery, lace, tailoring, draping, romanticism, and glamor. In the Milan collection, checks, prints, denim, and minidresses reflected sport and romanticism. The London collection included fringe, ruffles, floral patterns, flower patterns, and romanticism. The New York collections included vivid colors, neon colors, pastel colors, oversize silhouettes, bodysuits, and long dresses.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.7211-7218
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• 2015

Tens of thousands of malicious codes are generated on average in a day. New types of malicious codes are surging each year. Diverse methods are used to detect such codes including those based on signature, API flow, strings, etc. But most of them are limited in detecting new malicious codes due to bypass techniques. Therefore, a lot of researches have been performed for more efficient detection of malicious codes. Of them, visualization technique is one of the most actively researched areas these days. Since the method enables more intuitive recognition of malicious codes, it is useful in detecting and examining a large number of malicious codes efficiently. In this paper, we analyze the relationships between malicious codes and Native API functions. Also, by applying the word cloud with text mining technique, major Native APIs of malicious codes are visualized to assess their maliciousness. The proposed malicious code analysis method would be helpful in intuitively probing behaviors of malware.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.33-38
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• 2021

The convergence trend is the core of the 4th industrial revolution, and due to such expectations and possibilities, various countermeasures are being sought in diverse fields. This study conducted a quantitative analysis to identify the trend of convergence research over the past 10 years. Specifically, major research keywords were extracted, word cloud techniques were applied, and visualized to identify trends in academic research on convergence. To this end, research papers from 2012 to 2020 published in journal of digital convergence were investigated. The analysis period was divided into two periods: the former 4 years(2012-2015) and the latter 4 years(2016-2019) to confirm the difference in research trends. In addition, the research papers of 2020 were analyzed in order to more clearly understand the changes in the research trend of the last year due to the COVID-19. The results of this study are significant in that they can be used as useful basic data for future research and to understand research trends as keywords in the field of convergence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.231-244
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• 2022

With the improvement of people's living standards and the development of tourism, tourists have greater freedom in choosing destinations. Therefore, as an indicator of satisfaction with scenic spots, tourist comments are becoming increasingly prominent. This paper aims to compare and analyze the landscape image of the Five Great Mountains in China and provide specific strategies for its development. The online reviews of tourists on the Online Travel Agency (OTA) website about the Five Great Mountains from 2015 to 2018 are collected as research samples. The text analysis method and R language are used to analyze the content of the tourist reviews, while the high-frequency words in the word cloud are used for visual display. In addition, the entropy weight method is used to determine the index weight and tourist satisfaction is evaluated to understand the weaknesses of those scenic spots. The results of the study show that firstly, the tourist satisfaction with the Five Great Mountains is basically consistent with its popularity. Secondly, through weight analysis, tourists pay special attention to the landscape features and environmental health of the scenic area, so that relevant departments should focus on building the landscape characteristics and improving the environmental health of the scenic area. At the same time, the accommodation and service management of the scenic spot cannot be ignored. Finally, according to the analysis results, suggestions are made on how to improve the tourist satisfaction with the Five Great Mountains.

• Journal of Fashion Business
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• v.27 no.4
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• pp.50-66
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• 2023

The purpose of this study was to examine the word distribution and topic distribution of slow fashion appearing on YouTube in detail and identify the characteristics and aspects related to fashion design through big data analysis and content analysis methods. The specific research results were as follows. First, in the results of the word distribution analysis, "item" appeared the most, 203 times. Also, "one-piece" was a point to pay attention to, as the item had the highest frequency. Second, a total of 5 topics were defined in the topic distribution analysis: topic 1 was "vintage products," topic 2 was "fashion items," topic 3 was "eco-friendly," topic 4 was "life quality emphasis," and topic 5 was "prudent consumption." Third, looking at the relationship between word distribution and topic distribution above, Korean slow fashion on YouTube was actively selecting related design elements that express vintage images in clothing life regardless of trends. In addition, there was a tendency to pursue various basic and high-quality items. Other than those findings, basic items tended to be reinterpreted in various ways through styling methods matched to the vintage image. Lastly, the tendency of slow and small-volume production appeared to emphasize handicrafts and the cultural values of fashion products.