• 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.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.360-374
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• 2024

A personalized course recommendation algorithm based on deep learning in an online education cloud platform is proposed to address the challenges associated with effective information extraction and insufficient feature extraction. First, the user potential preferences are obtained through the course summary, course review information, user course history, and other data. Second, by embedding, the word vector is turned into a low-dimensional and dense real-valued vector, which is then fed into the compressed interaction network-deep neural network model. Finally, considering that learners and different interactive courses play different roles in the final recommendation and prediction results, an attention mechanism is introduced. The accuracy, recall rate, and F1 value of the proposed method are 0.851, 0.856, and 0.853, respectively, when the length of the recommendation list K is 35. Consequently, the proposed strategy outperforms the comparison model in terms of recommending customized course resources.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.153-171
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• 2019

Competition among cities has become fierce with decentralization and globalization, and each city tries to establish a brand image of the city to build its competitiveness and implement its policies based on it. At this time, surveys, expert interviews, etc. are commonly used to establish city brands. These methods are difficult to establish as sampling methods an empirical component, the biggest component of a city brand. In this paper, therefore, based on the precedent research's urban brand measurement and components, the words representing each city image property were extracted and relocated to five indicators to form the evaluation index. The constructed indicators have been validated through the review of three experts. Through the index, we analyzed the brands of four cities, Ulsan, Incheon, Yeosu, and Gyeongju, and identified the factors by using Topic Modeling and Word Cloud. This methodology is expected to reduce costs and monitor timely in identifying and analyzing urban brand images in the future.

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

• Journal of the Korean Society of Food Culture
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• v.34 no.4
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• pp.411-423
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• 2019

This study conducted qualitative research through in-depth interviews on the diffusion process of Korean food in accordance with the length of residence of Chinese students in Korea. As the analysis method, the qualitative analysis method such as NVivo12.0 was used, and the analysis was performed through word frequency, word cloud, and coding matrix. The images of taste of Korean food were revealed as 'Spicy', 'Sweet', and 'Light taste' by both short-term Chinese residents and long-term Chinese residents. The long-term Chinese residents showed their dissatisfaction with the institutional food, and they also pointed out the importance of the matter of cooking for quick adaptation to life in Korea. The long-term Chinese residents also thought of Korean food as 'High-fiber food', and this was influenced by the 'Less-oil' cooking method of Korean food, which is different from the cooking method of Chinese food. The length of residence was used as a main variable of this study, and it was one of the factors having positive effects on the diffusion of Korean food and acculturation. It would be difficult to generalize the results because this study used the convenience sampling method and snowball sampling.

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

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.891-897
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• 2022

In big data analysis, raw text data mostly exists in various unstructured data forms, so it becomes a structured data form that can be analyzed only after undergoing heuristic pre-processing and computer post-processing cleansing. Therefore, in this study, unnecessary elements are purified through pre-processing of the collected raw data in order to apply the wordcloud of R program, which is one of the text data analysis techniques, and stopwords are removed in the post-processing process. Then, a case study of wordcloud analysis was conducted, which calculates the frequency of occurrence of words and expresses words with high frequency as key issues. In this study, to improve the problems of the "nested stopword source code" method, which is the existing stopword processing method, using the word cloud technique of R, we propose the use of "general stopword corpus" and "user-defined stopword corpus" and conduct case analysis. The advantages and disadvantages of the proposed "unstructured data cleansing process model" are comparatively verified and presented, and the practical application of word cloud visualization analysis using the "proposed external corpus cleansing technique" is presented.

• Journal of the Korea Institute of Building Construction
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• v.24 no.3
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• pp.319-329
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• 2024

This study examined domestic and international regulations concerning concrete unit weight, along with an evaluation of unit weight in concrete poured on construction sites. Fluctuations in unit weight were observed to correlate with concrete quality issues such as material separation, bleeding, and latency. A word cloud analysis, centered on the concept of concrete quality, further highlighted the significant influence of unit weight. Comparative analysis between Korea and Japan revealed few substantial differences in unit weight management and measurement techniques. However, calculation of concrete unit weight at delivery, using the unit volume mass method, indicated considerable variability among random on-site samples. Notably, the unit weight often exceeded the recommended standard. These findings emphasize the necessity for strict adherence to unit weight standards by all stakeholders involved in concrete production and construction, including ready-mix concrete (REMICON) producers, construction firms, and inspectors. To ensure consistent quality of cast concrete on-site, the establishment of a more comprehensive and practical system is recommended, incorporating measures such as on-site inspections.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.49-63
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• 2024

Objective : The purpose of this study was to investigate parental perspectives on cognitive rehabilitation using a combination of phenomenological research methodology and word cloud analysis. Methods : Interviews were conducted with five parents of children with developmental disabilities. Word cloud analysis was conducted using Python, and five researchers analyzed the meaning units and themes using phenomenological methods. Words with high frequency were considered as a heuristic tool. Results : A total of 43 meaning units and nine components related to the phenomenon of cognitive rehabilitation were derived, and three themes were finalized. The main themes encompassed the definition of cognitive rehabilitation, challenges associated with cognitive rehabilitation, and factors influencing the selection of a cognitive rehabilitation institute. Cognitive rehabilitation emerged as a treatment focused on improving learning, daily functioning, and cognitive abilities in children with developmental disabilities. The perceived issues with cognitive rehabilitation pertained to treatment methods, therapist expertise, and associated costs. In addition, parents highlighted the importance of therapist expertise, humane personality, and affordability of cost and schedule when choosing a cognitive rehabilitation institute. Conclusion : Parents expressed expectations for substantial improvements in their children's daily functioning through cognitive rehabilitation. However, challenges were identified in clinical practices. Going forward, we expect that cognitive rehabilitation will evolve into a better therapeutic support service addressing the concerns raised by parents.

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