• 대한한방내과학회지
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• 제43권6호
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• pp.1075-1088
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• 2022

Objectives: The aim of this study is to analyze cancer research trends in traditional Korean medical journals indexed in the Korea Citation Index since 2000. Methods: Cancer research papers published in traditional Korean medical journals were searched in databases from inception to October 2022. The numbers of publications by journal and by year were descriptively assessed. After natural language processing, topic modeling (based on Latent Dirichlet allocation) and keyword network analysis were conducted. Results: This research trend analysis involved 1,265 papers. Six topics were identified by topic modeling: case reports on symptom management, literature reviews, experiments on apoptosis, herbal extract treatments of breast carcinoma cell lines, anti-proliferative effects of herbal extracts, and anti-tumor effects. Keyword network analysis found that the effects of herbal medicine were assessed in clinical and experimental studies, while acupuncture was mainly mentioned in clinical reports. Conclusions: Cancer research papers in traditional Korean medical journals have contributed to evidence-based medicine. Further experimental studies are needed to elucidate the effects of on different hallmarks of cancer. Rigorous clinical studies are needed to support clinical guidelines.

• 산업경영시스템학회지
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• 제45권1호
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• pp.53-70
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• 2022

Recently, due to the change to SASB(Sustainability Accounting Standards Board) and GRI(Global Reporting Initiative) Standards 2021, the paradigm for non-financial information disclosure is changing significantly, with the number of ESG topics and indicators that must be disclosed by industry from an autonomous material topic selection method. This study revealed that the number of compulsory topics in the oil and gas industry by GRI standards 2021 is up to 2.4 times higher than the average number of material topics disclosed when domestic companies publish sustainability reports using GRI Standards 2020. In the oil and gas industry, I analyzed the similarities and differences between the GRI standards 2021 and the ESG topics covered by SASB by environmental, social, economic, and governance areas. In addition, the materiality test process, which is different in GRI standards 2021, is introduced, and the issues included in the following 10 representative ESG-related initiatives are summarized into 62 and suggested improvement plans for materiality test used in the topic pool.

• 무역학회지
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• 제47권6호
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• pp.189-209
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• 2022

This study aims to analyze Latin America and the Caribbean papers published in Korea during the past 2000-2020 years. Through this study, it is possible to understand the main subject and direction of research in Korea's Latin America and the Caribbean area. As the research mythologies, this study uses the text mining and Social Network Analysis such as frequency analysis, several centrality analyses, and topic analysis. After analyzing the empirical results, there has been a tendency to change the key words and centrality coefficients between 2000-2010 and 2011-2020 years. During 2011-2020 years, the most frequent keywords were changed from Neoliberalism and culture to policy education, and economy related words. The degree and closeness centrality analyses appeared the higher frequency key words. However, the eigenvector centrality appeared very different from the order of frequency key words. The topic analysis shows that the culture, language, and Neoliberalism were the most important keywords during 2000-2010 years but economy, labor trade, industry, development became the most important keywords during 2011-2020 years in topics.

• 무역학회지
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• 제45권3호
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• pp.55-69
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• 2020

This study examines the research trends and knowledge structure of international trade studies using topic modeling method, which is one of the main methodologies of text mining. We collected and analyzed English abstracts of 1,868 papers of three Korean major journals in the area of international trade from 2003 to 2019. We used the Latent Dirichlet Allocation(LDA), an unsupervised machine learning algorithm to extract the latent topics from the large quantity of research abstracts. 20 topics are identified without any prior human judgement. The topics reveal topographical maps of research in international trade and are representative and meaningful in the sense that most of them correspond to previously established sub-topics in trade studies. Then we conducted a regression analysis on the document-topic distributions generated by LDA to identify hot and cold topics. We discovered 2 hot topics(internationalization capacity and performance of export companies, economic effect of trade) and 2 cold topics(exchange rate and current account, trade finance). Trade studies are characterized as a interdisciplinary study of three agendas(i.e. international economy, International Business, trade practice), and 20 topics identified can be grouped into these 3 agendas. From the estimated results of the study, we find that the Korean government's active pursuit of FTA and consequent necessity of capacity building in Korean export firms lie behind the popularity of topic selection by the Korean researchers in the area of int'l trade.

• 한국산업융합학회 논문집
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• 제27권2_2호
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• pp.343-356
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• 2024

Super app is an application that provides a variety of services in a unified interface within a single platform. With the acceleration of digital transformation, super apps are becoming more prevalent. This study aims to suggest service enhancement measures by analyzing the user review data before and after the transition to a super app. To this end, user review data from a payment-based super app(Shinhan Play) were collected and studied via topic modeling. Moreover, a matrix for assessing the importance and usefulness of topics is introduced, which relies on the eigenvector centrality of the inter-topic network obtained through topic modeling and the number of review recommendations. This allowed us to identify and categorize topics with high utility and impact. Prior to the transition, the factors contributing to user satisfaction included 'payment service,' 'additional service,' and 'improvement.' Following the transition, user satisfaction was associated with 'payment service' and 'integrated UX.' Conversely, dissatisfaction factors before the transition encompassed issues related to 'signup/installation,' 'payment error/response,' 'security authentication,' and 'security error.' Following the transition, user dissatisfaction arose from concerns regarding 'update/error response' and 'UX/UI.' The research results are expected to be used as a basis for establishing strategies to strengthen service competitiveness by making super app services more user-oriented.

• 한국의상디자인학회지
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• 제26권2호
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• pp.87-99
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• 2024

Freediving, an underwater leisure sport that involves diving without the use of a breathing apparatus, has gained popularity among younger demographics through the viral spread of images and videos on social media platforms. This study employs prominent Big Data analysis techniques, including text mining, Latent Dirichlet Allocation (LDA) topic analysis, and opinion mining to explore the keywords associated with freediving suits over the past five years. The research aims to analyze the rapidly evolving market trends of freediving suits and the increasingly complex and diverse consumer perceptions to provide foundational data for activating the freediving suit market and developing strategies for sustained growth. The study identified the keyword 'size' related to freediving suits and conducted opinion mining on 'freediving suit sizes'. Although the results showed a higher positive than negative sentiment, negative keywords were also extracted, indicating the need to understand and mitigate the negative factors associated with 'size'. The findings offer vital guidelines for the advancement of the freediving suit market and enhancing consumer satisfaction. This study is important as it contributes foundational data for continuous growth strategies of the freediving suit market.

• Journal of Information Technology Applications and Management
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• 제30권1호
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• pp.53-70
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• 2023

Artificial intelligence has become familiar with modern society, not the distant future. As artificial intelligence and machine learning developed more highly and became more complicated, it became difficult for people to grasp its structure and the basis for decision-making. It is because machine learning only shows results, not the whole processes. As artificial intelligence developed and became more common, people wanted the explanation which could provide them the trust on artificial intelligence. This study recognized the necessity and importance of explainable artificial intelligence, XAI, and examined the trends of XAI research by analyzing social networks and analyzing topics with IEEE published from 2004, when the concept of artificial intelligence was defined, to 2022. Through social network analysis, the overall pattern of nodes can be found in a large number of documents and the connection between keywords shows the meaning of the relationship structure, and topic modeling can identify more objective topics by extracting keywords from unstructured data and setting topics. Both analysis methods are suitable for trend analysis. As a result of the analysis, it was found that XAI's application is gradually expanding in various fields as well as machine learning and deep learning.

• 한국인터넷방송통신학회논문지
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• 제19권5호
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• pp.63-71
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• 2019

4차 산업혁명시대를 맞이하여 스마트팩토리의 구축에 관한 많은 연구가 진행되고 있다. 이러한 스마트팩토리의 구축과 관련된 다양한 기술들 중에서 핵심기술 중의 하나는 데이터의 송수신을 처리하는 IoT용 프로토콜 부문이다. 이와 관련하여 일반적으로 MQTT 프로토콜이 가장 많이 사용되고 있으나 기존의 MQTT 기술은 메시지의 우선순위 개념이 없기 때문에 실시간성을 요구하는 산업용 현장에 적용하기에는 다소 부족한 면이 있다. 특히 특정 설비의 고장발생에 따른 관련 설비 전체의 비상정지 등과 같은 긴급 상황에서는 긴급한 메시지의 우선순위 처리가 매우 중요하다. 이를 개선하기 위해 우선순위 기반 MQTT에 관한 연구도 일부 진행되고 있으나 이러한 연구들은 MQTT 표준 규격을 변형한 방식이기 때문에 실제 현장에서 사용하기에는 문제점을 안고 있다. 따라서 본 연구에서는 MQTT 표준을 준수하면서도 메시지의 우선순위 처리가 가능한 MQTT에 관련한 연구를 실시하고 이를 검증한다.

• 경영정보학연구
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• 제26권2호
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• pp.205-221
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• 2024

2023년 6월 공간 컴퓨팅이라는 용어가 애플 비전 프로 공개로 인해 대중들에게 본격적으로 인식되기 시작하였고, 2024년 2월 공식 출시를 기점으로 관심이 폭발적으로 증가하고 있다. 이제 막 시장이 개화된 상황에서 공간 컴퓨팅의 지속가능한 성장을 위해 대중들의 인식을 분석하고 근거 기반으로 산업계와 정부를 위한 적절한 대응 방향을 제시할 필요가 있다. 이에, 본 연구는 다양한 텍스트마이닝 기법을 이용하여 국내 대중들의 공간 컴퓨팅에 대한 인식을 탐색하였고, 분석 결과를 바탕으로 성공적인 시장 안착을 위한 전략 방향을 모색하였다. 결과적으로 공간 컴퓨팅에 대한 선도적 연구 수행과 새로운 연구방법론 제시, 이해관계자들이 활용할 수 있는 전략 및 정부 정책 방향을 제시했다는 점에서 본 연구의 의의가 있다.

• 디지털융복합연구
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• 제14권3호
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• pp.251-260
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• 2016

과학기술 및 R&D 연구자는 선행 연구와 그 개발 결과에 대해 조사 분석하는데 많은 시간을 소비한다. 그리고 최근에는 효과적인 정보검색을 위해 시맨틱 웹을 비롯한 다양한 검색기술을 제공하고 있으며, 특히 온톨로지를 이용한 검색기술은 가장 효과적인 방법으로 알려져 있다. 이에, 본 연구는 국가 R&D정보(사업 및 과제정보), 그 사업 및 과제 수행을 통한 성과물(논문, 특허, 보고서, 기술이전 정보 등), 그리고 사업 및 과제와 연관된 정보(동향, 연구자, 용어 정보 등)를 연계하여 지식베이스(RDF-Triple)를 모델링하고, 이를 지식맵 서비스로 구현하여 연구자에게 국가 R&D정보를 한 눈에, 한 곳에서 국가 R&D정보를 살펴볼 수 있게 하는 것이다. 이를 통해, 정책가(정책입안자)에게는 R&D 전략 수립 과정 및 의사 결정을 지원할 수 있으며, 연구자에게는 선행 연구에 대한 조사 분석 시간 단축 및 새로운 연구 주제를 도출할 수 있는 기회를 제공할 수 있다.