• Journal of the Korean Wood Science and Technology
• /
• 제51권6호
• /
• pp.458-469
• /
• 2023

Text mining techniques provide valuable insights into research information across various fields. In this study, text mining was used to identify research trends in wood science from 2012 to 2022, with a focus on representative journals published in Korea and Japan. Abstracts from Journal of the Korean Wood Science and Technology (JKWST, 785 articles) and Journal of Wood Science (JWS, 812 articles) obtained from the SCOPUS database were analyzed in terms of the word frequency (specifically, term frequency-inverse document frequency) and co-occurrence network analysis. Both journals showed a significant occurrence of words related to the physical and mechanical properties of wood. Furthermore, words related to wood species native to each country and their respective timber industries frequently appeared in both journals. CLT was a common keyword in engineering wood materials in Korea and Japan. In addition, the keywords "MDF," "MUF," and "GFRP" were ranked in the top 50 in Korea. Research on wood anatomy was inferred to be more active in Japan than in Korea. Co-occurrence network analysis showed that words related to the physical and structural characteristics of wood were organically related to wood materials.

• 한국의류학회지
• /
• 제47권5호
• /
• pp.804-821
• /
• 2023

This study examines current trends and perceptions of veganism and vegan fashion in Korea, China, and the United States. Using big data tools Textom and Ucinet, we conducted cluster analysis between keywords. Further, frequency analysis using keyword extraction and CONCOR analysis obtained the following results. First, the nations' perceptions of veganism and vegan fashion differ significantly. Korea and the United States generally share a similar understanding of vegan fashion. Second, the industrial structures, such as products and businesses, impacted how Korea perceived veganism. Third, owing to its ongoing sociopolitical tensions, the United States views veganism as an ethical consumption method that ties into activism. In contrast, China views veganism as a healthy diet rather than a lifestyle and associates it with Buddhist vegetarianism. This perception is because of their religious history and culinary culture. Fundamentally, this study is meaningful for using big data to extract keywords related to vegan fashion in Korea, China, and the United States. This study deepens our understanding of vegan fashion by comparing perceptions across nations.

• 문화기술의 융합
• /
• 제9권5호
• /
• pp.859-865
• /
• 2023

OTT 시장의 과열로 서비스 사업자들이 콘텐츠 개발에 주력하는 상황에서 시청자들의 능동적인 참여를 독려하는 인터랙티브 콘텐츠가 주목받고 있다. 그에 따라 인터랙티브 콘텐츠에 관한 연구 역시 활발히 이루어지고 있다. 본 연구는 온라인상의 비정형 데이터를 중심으로 텍스트 마이닝을 통해 인터랙티브 콘텐츠에 관한 분석을 목적으로 한다. 가중치에 따른 키워드 특징 도출, OTT와 인터랙티브 콘텐츠의 관계, 그리고 인터랙티브 콘텐츠의 트렌드 변화를 객관적인 데이터에 근거하여 '워드클라우드', '관계도 분석', 그리고 '키워드 트렌드'라는 세부 기법을 활용하여 연구 결과 및 함의점을 도출하였다.

• 디지털산업정보학회논문지
• /
• 제19권4호
• /
• pp.87-96
• /
• 2023

ChatGPT, a leader in generative AI, can use natural expressions like humans based on large-scale language models (LLM). The ability to grasp the context of the language and provide more specific answers by algorithms is excellent. It also has high-quality conversation capabilities that have significantly developed from past Chatbot services to the level of human conversation. In addition, it is expected to change the operation method of the tourism industry and improve the service by utilizing ChatGPT, a generative AI in the tourism sector. This study was conducted to explore ChatGPT trends and paradigms in tourism. The results of the study are as follows. First, keywords such as tourism, utilization, creation, technology, service, travel, holding, education, development, news, digital, future, and chatbot were widespread. Second, unlike other keywords, service, education, and Mokpo City data confirmed the results of a high degree of centrality. Third, due to CONCOR analysis, eight keyword clusters highly relevant to ChatGPT in the tourism sector emerged.

• Asia pacific journal of information systems
• /
• 제32권4호
• /
• pp.770-802
• /
• 2022

With the development of deep learning techniques, text mining is producing breakthrough performance improvements, promising future applications, and practical use cases across many fields. Likewise, even though several attempts have been made in the field of financial information, few cases apply the current technological trends. Recently, companies and government agencies have attempted to conduct research and apply text mining in the field of financial information. First, in this study, we investigate various works using text mining to show what studies have been conducted in the financial sector. Second, to broaden the view of financial application, we provide a description of several text mining techniques that can be used in the field of financial information and summarize various paradigms in which these technologies can be applied. Third, we also provide practical cases for applying the latest text mining techniques in the field of financial information to provide more tangible guidance for those who will use text mining techniques in finance. Lastly, we propose potential future research topics in the field of financial information and present the research methods and utilization plans. This study can motivate researchers studying financial issues to use text mining techniques to gain new insights and improve their work from the rich information hidden in text data.

• 디지털산업정보학회논문지
• /
• 제20권2호
• /
• pp.37-47
• /
• 2024

The food tech market, which uses artificial intelligence robots for the restaurant industry, is gradually expanding. Among them, the robot barista, a representative food tech case for the restaurant industry, is characterized by increasing the efficiency of operators and providing things for visitors to see and enjoy through a 24-hour unmanned operation. This research was conducted through text mining analysis to examine trends related to robot baristas in the restaurant industry. The research results are as follows. First, keywords such as coffee, cafe, certification, ordering, taste, interest, people, robot cafe, coffee barista expert, free, course, unmanned, and wine sommelier were highly frequent. Second, time, variety, possibility, people, process, operation, service, and thought showed high closeness centrality. Third, as a result of CONCOR analysis, a total of 5 keyword clusters with high relevance to the restaurant industry were formed. In order to activate robot barista in the future, it is necessary to pay more attention to functional development that can strengthen its functions and features, as well as online promotion through various events and SNS in the robot barista cafe.

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

• 한국의류산업학회지
• /
• 제14권4호
• /
• pp.614-628
• /
• 2012

The purpose of this study was to analyze research trends and make suggestions regarding the future of information technology (IT) in the fashion industry. In this study, 437 papers written regarding IT fashion from five major journals published between 2000 and 2011 were examined. The research areas were then organized by subject and keyword, and divided into 16 high-context categories. Two IT fashion maps were constructed, one from a fashion consumer's perspective, and the other based on the fashion industry's supply chain. This study identified important trends in IT fashion such as: 3D scanners, 3D digital renderings of the human form, 3D digital garments, smart garments, mass customization, production automation, online shopping, home shopping, online communities, e-commerce, digital media, virtual reality, e-tail, the digital generation, E-CRM, and education. Data from body scans was collected and applied to production, and research on smart textiles was also carried out. As for IT fashion's service areas, the majority of the research focused on online shopping or online communication. Additionally, research done on avatars and cyber space, and studies on social networking services are shown. The results of this study indicated that a new field of research has opened and that current research has been developing. Also, this study showed what is needed to expand and strengthen IT fashion.

• 한국콘텐츠학회논문지
• /
• 제20권10호
• /
• pp.688-701
• /
• 2020

본 연구는 시각장애인 대상의 인공지능 관련 연구 동향을 살펴보기 위해 1993년부터 2020년 8월까지 국내·외 논문 총 68편을 선정하여 연도별 논문 게재 수, 연구방법, 연구주제, 키워드 분석 현황, 연구유형, 구현방법별 비교·분석하였다. 연구결과, 연구기간 내 논문 편수는 꾸준히 증가하는 것처럼 보였으나 국내 연구의 경우에는 2016년도 이후에 활발해진 것을 알 수 있었다. 연구방법으로는 국내·외 연구 모두 개발연구가 89.7%를 차지했고, 키워드는 국내 연구에서는 Visually impaired, Deep learning, Assistive device 순이였으며 국외 연구에서는 Visually impaired, Deep learning, Artificial intelligence 순으로 단어 빈도순에서 차이를 보였다. 연구유형은 국내·외 모두 설계, 개발, 구현이 대부분을 차지했으며 구현방법으로는 국내 연구의 구현방법으로는 System 13.2%, Solution 7.4%, App. 4.4% 순이였으며 국외 연구의 구현방법으로는 System 32.4%, App.13.2%, Device 7.4%로 다소 차이를 보였다. 구현방법의 적용 기술로는 국내 연구는 YOLO 2.7%, TTS 2.1%, Tensorflow 2.1% 순이였으며 국외 연구에서는 CNN 8.0%, TTS 5.3%, MS-COCO 4.3% 순으로 사용횟수가 높았다. 본 연구는 시각장애인 대상의 인공지능 관련 연구 동향을 비교·분석하여 국내·외 연구의 현주소를 바로 알고 앞으로 시각장애인을 위한 인공지능 연구의 방향을 제시하고자 하였다.

• 정보관리학회지
• /
• 제34권4호
• /
• pp.7-32
• /
• 2017

최근 들어 다양한 분야에서 딥러닝이 혁신적인 기계학습 기법으로 급속하게 확산되고 있다. 이 연구에서는 딥러닝 연구동향을 분석하기 위해서 자아 중심 주제 인용분석 기법을 변형하여 응용해보았다. 이를 위해 Web of Science에서 'deep learning'으로 탐색하여 검색된 문헌 중 소수의 씨앗 문헌으로부터 인용 관계를 통해 분석 대상 문헌을 확보하는 방법을 시도하였다. 씨앗 문헌을 인용하는 최근 논문들을 딥러닝 분야의 현행 연구를 반영하는 자아 문헌집합으로 설정하였다. 자아 문헌으로부터 빈번히 인용된 선행 연구들은 딥러닝 분야의 연구 주제를 나타내는 인용 정체성 문헌집합으로 설정하였다. 자아 문헌집합에 대해서는 공저 네트워크 분석을 비롯한 정량적 분석을 실시하여 주요 국가와 연구 기관을 파악하였다. 인용 정체성 문헌들에 대해서는 동시인용 분석을 실시하고, 도출된 문헌 군집을 인용하는 주요 키워드인 인용 이미지 키워드를 파악하여 주요 문헌과 주요 연구 주제를 밝혀내었다. 마지막으로 특정 주제에 대한 인용 영향력이 성장하는 추세를 반영하는 인용 성장지수 CGI를 제안하고 측정하여 딥러닝 분야의 선도 연구 주제가 변화하는 동향을 밝혔다.