• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.273-280
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• 2020

Automatic Static Analysis Tools help developers to quickly find potential defects in source code with less effort. However, the tools reports a large number of false positive warnings which do not have to fix. In our study, we proposed an artificial neural network-based warning classification method using topic models of source code blocks. We collect revisions for fixing bugs from software change management (SCM) system and extract code blocks modified by developers. In deep learning stage, topic distribution values of the code blocks and the binary data that present the warning removal in the blocks are used as input and target data in an simple artificial neural network, respectively. In our experimental results, our warning classification model based on neural network shows very high performance to predict label of warnings such as true or false positive.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.199-211
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• 2019

This study analyzed the research trends of college students' entrepreneurship in 172 scholarly articles in the registered journals of the Korea Research Foundation from 2010 to 2018. The results of this study are as follows: First, the research areas and topics on university students' entrepreneurship focuses on not only characteristics of entrepreneurship and entrepreneur but also entrepreneurship education. Also, the research method was dependent on the quantitative research method coupled with the statistic techniques such as descriptive statistics, correlation, t-test, ANOVA, regression analysis, and structural equation modeling. In future research, it is necessary to expand research areas to startup idea design, startup business environment and policies. Also, it is necessary to explore various variables related to entrepreneurship, not focusing on specific variables such as entrepreneurship, entrepreneurship education as well as to analyze meta analysis of the relationship between the variables influencing on the entrepreneurial intention. In addition, qualitative research and mixed research are needed to explore the process of developing entrepreneurship and the factors affecting the process of entrepreneurship.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.147-163
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• 2023

Recently, there has been an increase in the research and development of automated vehicles worldwide. Research focused on automated vehicles in Korea is steadily progressing as a national R&D project. Since automated driving technology comprises diverse technology fields, it is necessary to identify the current position of the research. In this study, we propose a methodology for analyzing research trends using the NTIS data. In addition, we review the effectiveness of the currently developed research trend methodology by deriving primary keywords and major topics using the proposed method. We expect that the methodology developed in this study can be applied to identify and analyze future automated vehicle research trends.

• Journal of Home Health Care Nursing
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• v.30 no.2
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• pp.141-154
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• 2023

Purpose: This study aimed to explore the social perception of visiting nursing before and after coronavirus disease (COVID-19). Methods: This survey-based study used online big data for comparative analysis by classifying the keywords related to visiting nursing searched on domestic portal sites before and after COVID-19. Results: According to the results of analyzing the Intertopic Distance Map based on Latent Dirichlet Allocation in this study, four topics were extracted, two each before and after COVID-19. The first topic before the COVID-19 period was termed "the expansion of visiting nursing subjects and services visiting nursing," while the second was termed "visiting nursing," which is related to customized welfare. The first topic after the COVID-19 period was termed "the suspension and resumption of visiting nursing services," while the second was "the development of a non-face-to-face home visit healthcare system". Conclusion: The results of this study can be used as useful reference data to contribute to future medical service delivery system reform policies starting at the end of COVID-19 and the revitalization of community care for visiting nursing.

• Journal of the Korean Society of Food Culture
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• v.38 no.1
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• pp.1-14
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• 2023

This study was conducted to explore the change in the market issues on HMR (Home Meal Replacements) using local foods after the COVID-19 outbreak. Online text data were collected from internet news, social media posts, and web documents before (from January 2016 to December 2019) and after (from January 2020 to November 2022) the COVID-19 outbreak. TF-IDF analysis showed that 'Trend', 'Market', 'Consumption', and 'Food service industry' were the major keywords before the COVID-19 outbreak, whereas 'Wanju-gun', 'Distribution', 'Development', and 'Meal-kit' were main keywords after the COVID-19 outbreak. The results of topic modeling analysis and categorization showed that after the COVID-19 outbreak, the 'Market' category included 'Non-face-to-face market' instead of 'Event,' and 'Delivery' instead of 'Distribution'. In the 'Product' category, 'Marketing' was included instead of 'Trend'. Additionally, in the 'Support' category, 'Start-up' and 'School food service' appeared as new topics after the COVID-19 outbreak. In conclusion, this study showed that meaningful change had occurred in market issues on HMR using local foods after the COVID-19 outbreak. Therefore, governments should take advantage of such market opportunity by implementing policy and programs to promote the development and marketing of HMR using local foods.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.91-110
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• 2021

In the face of the prolonged Covid-19, this study conducted a network analysis to propose the policy direction for the Korean National Assembly to go forward. Using COVID-19 news articles, various types of networks were created and analyzed for the parliamentary activities of the Korean National Assembly related to Covid-19. Specifically, we utilize the co-occurrence and keyword information to generate two types of parliamentary networks: co-occurrence-based network and content-based network. In addition, a topic keyword-driven parliamentary network was constructed by using topic modeling. The results of the study are as follows. First, lawmakers in the ruling party had a wide range of topics regarding Covid-19, while lawmakers from other political parties had a limited number of issues covered. Next, a few representative legislators were identified as influential actors in most of the centrality indicators. Based on the research results, cooperation on diverse agendas related to Covid-19 should be promoted between lawmakers from various political parties. And representative legislators from both major parties should play a crucial role as intermediaries to increase communication between them.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.1
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• pp.145-166
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• 2023

This study aims to analyze the research trends of English-language journals in Korean studies published in Korea. Data were collected from four English journals in Korean studies indexed in A&HCI and SCOPUS. A total of 1,840 were selected, including 768 articles of the Korea Journal, 466 articles of The Review of Korean Studies, 285 articles of the Seoul Journal of Korean Studies, and 321 articles of the Acta Koreana, in connection with content analysis, author analysis, author keyword frequency analysis, and topic modeling. In results, the domain research of Korean studies is Humanities, followed by Social Science, and Arts and Kinesiology. These three sectors have grown significantly in publishing numbers since 2000. The subject period of the study is in the order of the modern period, late Joseon, and Japanese colonial period. Authors from domestic affiliations made up 73.34% of the total, but the proportion of authors belonging to foreign institutions continued to increase. As for author keywords, 'Korea'(41), 'Buddhism'(20), 'Koreanwar'(18), and 'Joseon'(18) were derived as top keywords. In topic modeling, six topics were identified; 'Korean culture, cultural transmission,' 'Korean modern political history,' 'Korean social democratization process,' 'Japanese colonial period,' 'Korean religious philosophy,' and 'Korean ancient history.' Through this study, it was possible to identify the interests in and research areas of the recent international academic community of Korean studies.

• Journal of The Korean Association For Science Education
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• v.44 no.3
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• pp.231-248
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• 2024

This study developed a chatbot for first-year high school students, employing open-source software and the Korean Sentence-BERT model for AI-powered document classification. The chatbot utilizes the Sentence-BERT model to find the six most similar Q&A pairs to a student's query and presents them in a carousel format. The initial dataset, built from online resources, was refined and expanded based on student feedback and usability throughout over the operational period. By the end of the 2023 academic year, the chatbot integrated a total of 30,819 datasets and recorded 3,457 student interactions. Analysis revealed students' inclination to use the chatbot when prompted by teachers during classes and primarily during self-study sessions after school, with an average of 2.1 to 2.2 inquiries per session, mostly via mobile phones. Text mining identified student input terms encompassing not only science-related queries but also aspects of school life such as assessment scope. Topic modeling using BERTopic, based on Sentence-BERT, categorized 88% of student questions into 35 topics, shedding light on common student interests. A year-end survey confirmed the efficacy of the carousel format and the chatbot's role in addressing curiosities beyond integrated science learning objectives. This study underscores the importance of developing chatbots tailored for student use in public education and highlights their educational potential through long-term usage analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.670-681
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• 2016

Recently, based on Internet and mobile environments, the Fintech industry that fuses finance and IT together has been rapidly growing and Fintech services armed with simplicity and convenience have been leading the conversion of all financial services into online and mobile services. However, despite the rapid growth of the Fintech industry, few studies have classified Fintech technologies into detailed technologies, analyzed the technology development trends of major market countries, and supported technology planning. In this respect, using Fintech technological data in the form of unstructured data, the present study extracts and defines detailed Fintech technologies through the topic modeling technique. Thereafter, hot and cold topics of the derived detailed Fintech technologies are identified to determine the trend of Fintech technologies. In addition, the trends of technology development in the USA, South Korea, and China, which are major market countries for major Fintech industrial technologies, are analyzed. Finally, through the analyses of networks between detailed Fintech technologies, linkages between the technologies are examined. The trends of Fintech industrial technologies identified in the present study are expected to be effectively utilized for the establishment of policies in the area of the Fintech industry and Fintech related enterprises' establishment of technology strategies.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.59-76
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• 2023

In this study, we tried to find out port safety from various perspectives through news data that can be easily accessed by the general public and domestic academic journal data that reflects the insights of port researchers. Non-negative Matrix Factorization(NMF) based topic modeling was conducted using Python to derive the main topics for each data, and then semantic analysis was conducted for each topic. The news data mainly derived natural and environmental factors among port safety risk factors, and the academic journal data derived security factors, mechanical factors, human factors, environmental factors, and natural factors. Through this, the need for strategies to strengthen the safety of domestic ports, such as strengthening the resilience of port safety, improve safety awareness to broaden the public's view of port safety, and conduct research to develop the port industry environment into a safe and specialized mature port. As a result, this study identified the main factors to be improved and provided basic data to develop into a mature port with a port safety culture.