• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.456-466
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• 2015

This study is focusing to the keyword and blog advertising marketing services that are implementing a viral marketing utilizing keyword searches of the search portal and advertiser's blogs with convergent way. Through a case study for the company operating the service to pinpoint consumers to the advertisers site by indirect exposure via keyword advertising blog at the top of the search results, we analyzed the primitive service operation model on transactional relationship between the business players. We have a research purpose to generate improvement alternatives for the company's keyword advertising marketing services and operation solution using the survey study on the service quality perception and the perceptional gap between user groups. As results of study, we founded 4 types of the service solution and 4 models of service operating architecture on the transactional relations, and we recommended some improvements on the service and solution operation based on the SERVQUAL questionnaire analysis of the difference between the ads sponsor group and ads agency group.

• Journal of Korean Elementary Science Education
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• v.39 no.2
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• pp.255-267
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• 2020

Students' engagement is important for meaningful learning and it has multifaceted aspects for their science learning. This study investigated elementary students' perceptions of science learning engagement. The subjects of this study were 341 4^th to 6^th elementary students. The survey questionnaires were 5-Likert scale questions and free response questions on science learning engagement. The results showed that elementary students' perceptions of behavioral engagement were higher than emotional and cognitive engagement. Keyword network analysis with NetMiner program showed that the frequent key words of science learning engagement were 'experiment', 'listening', and 'teachers' explanation', which were mostly the behavioral types of engagement. The degree centrality and eigenvector centrality of these key words appeared high. 'Interest', which is emotional engagement, were also one of the frequent key words, but the centralities of this word were relatively low. The Frequent key words of science learning disengagement were mostly related with off-tasks, not doing expected behaviors and negative emotions about science and science learning. Educational implications on science learning engagement were discussed.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.521-526
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• 2017

Data format of Big data is diverse and vast, and its generation speed is very fast, requiring new management and analysis methods, not traditional data processing methods. Textual mining techniques can be used to extract useful information from unstructured text written in human language in online documents on social networks. Identifying trends in the message of politics, economy, and culture left behind in social media is a factor in understanding what topics they are interested in. In this study, text mining was performed on online news related to a given keyword using topic - oriented analysis technique. We use Latent Dirichiet Allocation (LDA) to extract information from web documents and analyze which subjects are interested in a given keyword, and which topics are related to which core values are related.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.27 no.2
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• pp.210-218
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• 2020

Purpose: The purpose of this study was to analyze research trends, using the keyword home health care, in articles published in the Journal of Korean Academic Society of Home Health Care Nursing over the past 10 years. Methods: An analysis was conducted of 50 home health care-based studies chosen from among the 206 studies published in the Journal of Korean Academic Society of Home Health Care Nursing from 2010 to 2019. The analysis focused on research methodology and keyword. Descriptive statistics were used to examine the frequency distribution of research methods and keywords. Results: Study participation was mainly focused on nurses (52.0%). Most of the studies used quantitative methods (96.0%), and 43 studies (86.0%) used self-report structured questionnaires. The most commonly used data analyses methods were descriptive statistics, t-test, analysis of variance, correlation, and regression. Major keywords were home health nursing, elderly care facility, visiting nurse, home care service, home healthcare nurse, home care agencies, long-term care, and home care. Conclusion: The results of this study identified current trends and interests in the Journal of Korean Academic Society of Home Health Care Nursing. This study suggests that future studies include a variety of research methods and maintain appropriate standards of research ethics.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.59-69
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• 2010

With the growing number of web services, there arise issues of finding suitable services. But, the traditional keyword search method is insufficient for two reasons: (1) this does not capture the underlying semantics of web services. (2) this does not suffice for accurately specifying users' information needs. In order to overcome limitations of this keyword search method, we propose a novel syntactic analysis and ontology learning method. The syntactic analysis method gives us a breadth of coverage for common terms, while the ontology learning method gives a depth of coverage by providing relationships. By combining these two methods, we hope to improve both the recall and the precision. We describe an experimental study on a collection of 508 web services that shows the high recall and precision of our method.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.115-128
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• 2022

The purpose of this study is to conduct keyword trend analysis using articles data on the impact of Covid-19 in the aviation in dustry. In this study, related articles were extracted centering on the keyword "Airline" by dividing the period of 6months before and after Covid-19 occurrence. After that, Topic modeling(LDA) was performed. Through this, The main topic was extracted in the event of an epidemic such as Covid-19, It is expected to be used as primary data to predict the aviation industry's impact when occurrence like Covid-19.

• Journal of Korean Medicine Rehabilitation
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• v.34 no.1
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• pp.49-64
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• 2024

Objectives By bibliographically analyzing acupuncture treatment studies for temporomandibular disorders over the past 20 years, we found an overview of global trends and a new perspective on future research directions. Methods We searched on the Web of Science webpage through the formula (TS=[temporomandibular] OR TS=[craniomandibular] OR TS=[jaw]) AND (TS=[^*acupuncture] OR TS=[dry needl^*] OR TS=[warm needl^*] OR TS=[thread embed^*]) AND (PY=[2003-2022]). And it was analyzed by year, research field, academic journal, country, research institute, author, and keyword. Results 194 papers were searched, and 92 papers were finally selected. The number of papers published over the past 20 years has been on the rise. Research has been the most active in the field of Dentistry Oral Surgery Medicine. Brazil published the most papers. And by institution, Universidade de Sao Paulo published the most papers. Among the authors, Fernández-de-las-Peñas has published the most papers. In the analysis by keyword, the top five keywords were temporomandibular joint disorder, acupuncture, myofascial pain, pain and management. Conclusions This study will provide useful guidelines for setting the direction of research by referring to the research status and keyword analysis when conducting research on the acupuncture on temporomandibular disorder in the future.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.187-192
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• 2023

In this study, trends in ICT education were investigated by analyzing the frequency of appearance of keywords related to machine learning and using conversion of iteration correction(CONCOR) techniques. A total of 304 papers from 2018 to the present published in registered sites were searched on Google Scalar using "ICT education" as the keyword, and 60 papers pertaining to ICT education were selected based on a systematic literature review. Subsequently, keywords were extracted based on the title and summary of the paper. For word frequency and indicator data, 49 keywords with high appearance frequency were extracted by analyzing frequency, via the term frequency-inverse document frequency technique in natural language processing, and words with simultaneous appearance frequency. The relationship degree was verified by analyzing the connection structure and centrality of the connection degree between words, and a cluster composed of words with similarity was derived via CONCOR analysis. First, "education," "research," "result," "utilization," and "analysis" were analyzed as main keywords. Second, by analyzing an N-GRAM network graph with "education" as the keyword, "curriculum" and "utilization" were shown to exhibit the highest correlation level. Third, by conducting a cluster analysis with "education" as the keyword, five groups were formed: "curriculum," "programming," "student," "improvement," and "information." These results indicate that practical research necessary for ICT education can be conducted by analyzing ICT education trends and identifying trends.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.245-256
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• 2022

The purpose of this study is to provide comprehensive insights on the current research trends in entrepreneurship based on topic modeling and keyword co-occurrence analysis. This study queried Web of Science database with 'entrepreneurship' and collected 14,953 research articles between 2002 and 2021. The study used R program for topic modeling and VOSviewer program for keyword co-occurrence analysis. The results of this study are as follows. First, as a result of keyword co-occurrence analysis, 5 clusters divided: entrepreneurship and innovation cluster, entrepreneurship education cluster, social entrepreneurship and sustainability cluster, enterprise performance cluster, and knowledge and technology transfer cluster. Second, as a result of the topic modeling analysis, 12 topics found: start-up environment and economic development, international entrepreneurship, venture capital, government policy and support, social entrepreneurship, management-related issues, regional city planning and development, entrepreneurship research, and entrepreneurial intention. Finally, the study identified two hot topics(venture capital and entrepreneurship intention) and a cold topic(international entrepreneurship). The results of this study are useful to understand current research trends in entrepreneurship research and provide insights into research of entrepreneurship.

• Journal of Navigation and Port Research
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• v.38 no.6
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• pp.607-614
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• 2014

This article aims to explore and discuss research trends in global cruise industry using keyword network analysis. We visualize keyword networks in each of four groups of 1982-1999, 2000-2004, 2005-2009, 2010-2014 based on the top 20 keyword nodes' degree centrality and betweenness centrality which are selected among four centrality measurements, comparing them with frequency order. The article shows that keyword frequency collected from 240 articles published in international journals is subject to Zipf's law and nodes degree distribution also exhibits power law. We try to find out research trends in global cruise industry to change some important keywords diachronically, visualizing several networks focusing on the top two keywords, cruise and tourism, belonging to all the four year groups, with high degree and betweenness centrality values. Interestingly enough, a new node, China, connecting the top most keywords, appears in the most recent period of 2010-2014 when China has emerged as one of the rapid development countries in global cruise industry. Therefore keyword network analysis used in this article will be useful to understand research trends in global cruise industry because of increase and decrease of numbers of network types in different year groups and the visual connection between important nodes in giant components.