• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.105-111
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• 2022

Multiple-choice survey types have been mainly performed to analyze students' needs for online classes. However, in order to analyze the exact needs of students, unstructured data analysis by answer for essay question is required. Big data is applied in various fields because it is possible to analyze unstructured data. This study aims to investigate and analyze what students want subjects or topics for software lecture in general education that process on non-face-to-face online teaching methods. As for the experimental method, keyword analysis and association analysis of big data were performed with unstructured data by giving a subjective questionnaire to students. By the result, we are able to know the keyword what the students want for software lecture, so it will be an important data for planning and designing software lecture of liberal arts in the future as students can grasp the topics they want to learn.

• Journal of dental hygiene science
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• v.22 no.3
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• pp.131-138
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• 2022

Background: The purpose of this study was to analyze research trends in articles published in the Journal of Dental Hygiene Science over the past decade. Methods: From 2011 to 2020, 653 studies were reviewed using a keyword analysis. Contents such as academic classification, research type, research method, research topic, data collection method, data analysis method, and financial support were analyzed. Results: Analysis by school type showed 34.2% of clinical dental hygiene studies, 23.3% of educational dental hygiene studies, 22.8% of basic dental hygiene studies, 10.0% of other field studies, and 9.8% of social dental hygiene studies. By type of study, quantitative studies were the most common at 69.5%. Regarding data collection methods, 45.8% of the studies that used surveys were the most common. The subjects of the study were 20.1% experimental studies, 15.6% general adults, and 15.0% dental hygienists. Regarding the data analysis method, 49.3% of the studies that conducted frequency analysis were the most common. The total number of keywords was 2,390, with 107 (4.48%) being 'dental hygienists.' Next, oral health was the most common with 67 (2.80%) articles, followed by 31 for the elderly (1.30%), 25 for dental hygiene students (1.05%), and 24 for stress (1.00%). Conclusion: For academic development of dental hygiene, it is necessary to explore the diversity of academic topics based on the results of this study. It is necessary to find a way to spread the research results so that the published research can be used for the academic development of dental hygiene.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.53-59
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• 2022

The purpose of this study is to examine the factors related to learning through analysis of domestic research trends in literacy and to present the direction of literacy education. Research papers from 1993 to February 2022 were collected using RISS. 'Literacy' and 'Education' were used as search keywords, and 200 papers were selected for analysis. As a result of analysis using keyword network analysis, 118 keywords appeared at least three times out of a total of 810 keywords. The order of the keywords with the highest frequency is 'digital literacy', 'media literacy', and 'elementary school'. The following direction was suggested through the analysis results. First, it is required to establish an online teaching and learning resource platform and link it with education policy. Second, it is necessary to set literacy competencies and seek ways to improve competencies. Third, a digital-based convergence education model should be developed. This study is meaningful in that it analyzed the most recent literacy studies and suggested the direction of literacy education.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.467-480
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• 2022

This paper aimed to explore research trends for the conceptualization of IT humanities. Reflecting domestic and international references which focused on the possibility of the integration of digital technology and humanities, the authors examined the beginning, background, and relevant concepts of IT humanities to figure out the meaning and the research trends. In addition, using the search word "IT humanities," the authors analyzed network topics of the keywords retrieved from 1,566 KCI and 64 SCI journal articles published since 2001. The concept of IT humanities in the previous studies has tended to associate with competencies that allow considering various fields of IT based on the lens of humanities perspectives. The result of the topic modeling revealed four groups as fields to be integrated with IT humanities, methods of implementation, connections of literature or culture, and creations of IT humanities. Instead of instrumentalization or merger by one stance of IT or humanities, it is imperative to collaboratively work for the generation of a new viewpoint through mutual respect of disciplines.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.1-8
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• 2009

Learning user's preference is a key issue in intelligent system such as personalized service. The study on user preference model has adapted simple user preference model, which determines a set of preferred keywords or topic, and weights to each target. In this paper, we recommend multi-perspective user preference model that factors sentiment information in the model. Based on the topicality and sentimental information processed using natural language processing techniques, it learns a user's preference. To handle timc-variant nature of user preference, user preference is calculated by session, short-term and long term. User evaluation is used to validate the effect of user preference teaming and it shows 86.52%, 86.28%, 87.22% of accuracy for topic interest, keyword interest, and keyword favorableness.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.193-198
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• 2023

We study a learner-customized lecture recommendation project using deep learning. Recommendation systems can be easily found on the web and apps, and examples using this feature include recommending feature videos by clicking users and advertising items in areas of interest to users on SNS. In this study, the sentence similarity Word2Vec was mainly used to filter twice, and the course was recommended through the Surprise library. With this system, it provides users with the desired classification of course data conveniently and conveniently. Surprise Library is a Python scikit-learn-based library that is conveniently used in recommendation systems. By analyzing the data, the system is implemented at a high speed, and deeper learning is used to implement more precise results through course steps. When a user enters a keyword of interest, similarity between the keyword and the course title is executed, and similarity with the extracted video data and voice text is executed, and the highest ranking video data is recommended through the Surprise Library.

• Journal of Korean Library and Information Science Society
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• v.54 no.3
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• pp.223-248
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• 2023

This study was conducted to compare and analyze trends in research on reading ability. To do this, collecting articles searched for 'reading ability', a keyword network analysis was performed based on the author's keyword. As a result of the analysis, it was found that the terms were used interchangeably in studies related to reading education at universities. In the study related to reading ability 1, the main research areas are school library, school librarian, information literacy, self-directed learning, and information service. In the study related to reading ability 2, the main research areas are children's early literacy, related reading difficulty and disability. In addition, studies on reading evaluation are being conducted in both areas, but not much activation has been performed. Studies involving adolescents show limited activity in both areas.

• Journal of Korean Academy of Rural Health Nursing
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• v.18 no.2
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• pp.113-124
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• 2023

Purpose: The number of households vulnerable to isolation increases rapidly as social ties decrease, raising concerns about the associated increase in lonely deaths. This study aimed to identify issues related to lonely deaths by analyzing South Korean news articles; and to provide evidence for their use in preventing and managing lonely deaths via community nursing. Methods: This exploratory study analyzed the structure and trends of meaning of lonely deaths by identifying the association between keywords in news articles and lonely deaths. In this study, we searched for all news articles on lonely deaths, covering the period from January 1, 2010, to May 31, 2023. Data preprocessing and purification were conducted, followed by top-keyword extraction, keyword network analysis and topic modeling. The retrieved articles were analyzed using R and Python software. Results: Four main topics were identified: "discovering and responding to lonely death cases", "lonely deaths ending in lonely funerals", "supportive policies to prevent lonely deaths among of older adults", and "local government activities to prevent lonely deaths and support vulnerable populations." Conclusion: Based on these findings, it can be concluded that lonely death is a complex social phenomenon that can be prevented if society shows concern and care. Education related to lonely deaths should be included in nursing curricula for concrete action plans and professional development.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2023.04a
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• pp.40-40
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• 2023

Atopic dermatitis is a chronic inflammatory skin diseases caused by skin barrier dysfunction. Allium victoralis var. Platyphyllum (AVP) is a perennial plant used as vegetable and herbal medicine. The purpose of this study was to suggest that AVP is a new cosmetic material by examining the effects of AVP on the skin barrier and inflammatory response. A bibliometric network analysis was performed through keyword co-occurrence analysis by extracting author keyword from 69 articles retrieved from SCOPUS. We noted the anti-inflammatory activity shown by the results of clustering and mapping from network visualization analysis using VOSviewer software tool. HPLC-UV analysis showed that AVP contains 0.12 ± 0.02 mg/g of chlorogenic acid and 0.10 ± 0.01 mg/g of gallic acid. AVP at 100 ㎍/mL was shown to increase the mRNA levels of filaggrin and involucrin related to skin barrier function by 1.50-fold and 1.43-fold, respectively. In the scratch assay, AVP at concentrations of 100 ㎍/mL and 200 ㎍/mL significantly increased the cell migration rate and narrowed the scratch area. In addition, AVP suppressed the increase of inflammation-related factors COX-2 and NO and decreased the release of β-hexosaminidase. This study suggests that AVP can be developed as a functional cosmetic material for atopy management through skin barrier protection effects, anti-inflammatory and anti-itch effects.

• Fashion & Textile Research Journal
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• v.25 no.5
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• pp.549-559
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• 2023

Along with the transition to the fourth industrial revolution, the possibility of metaverse-based innovation in the fashion field has been confirmed, and various applications are being sought. Therefore, this study performs meaning structure analysis and discusses the prospects of meta fashion using big data. From 2020 to 2022, data including the keyword "metaverse + fashion design" were collected from portal sites (Naver, Daum, and Google), and the results of keyword frequency, N-gram, and TF-IDF analyses were derived using text mining. Furthermore, network visualization and CONCOR analysis were performed using Ucinet 6 to understand the interconnected structure between keywords and their essential meanings. The results were as follows: The main keywords appeared in the following order: fashion, metaverse, design, 3D, platform, apparel, and virtual. In the N-gram analysis, the density between fashion and metaverse words was high, and in the TF-IDF analysis results, the importance of content- and technology-related words such as 3D, apparel, platform, NFT, education, AI, avatar, MCM, and meta-fashion was confirmed. Through network visualization and CONCOR analysis using Ucinet 6, three cluster results were derived from the top emerging words: "metaverse fashion design and industry," "metaverse fashion design and education," and "metaverse fashion design platform." CONCOR analysis was also used to derive differentiated analysis results for middle and lower words. The results of this study provide useful information to strengthen competitiveness in the field of metaverse fashion design.