• Title/Summary/Keyword: Trend keyword

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Technology Forecasting using Bayesian Discrete Model (베이지안 이산모형을 이용한 기술예측)

  • Jun, Sunghae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.27 no.2
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    • pp.179-186
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    • 2017
  • Technology forecasting is predict future trend and state of technology by analyzing the results so far of developing technology. In general, a patent has novel information about the result of developed technology, because the exclusive right of technology included in patent is protected for a time period by patent law. So many studies on the technology forecasting using patent data analysis has been performed. The patent keyword data widely used in patent analysis consist of occurred frequency of the keyword. In most previous researches, the continuous data analyses such as regression or Box-Jenkins Models were applied to the patent keyword data. But, we have to apply the analytical methods of discrete data for patent keyword analysis because the keyword data is discrete. To solve this problem, we propose a patent analysis methodology using Bayesian Poisson discrete model. To verify the performance of our research, we carry out a case study by analyzing the patent documents applied by Apple until now.

Research on major technology trends in the field of financial security through Korea and foreign patent data analysis (국내외 특허 데이터 분석을 통한 금융보안 분야 주요 기술 동향 분석연구)

  • Chae, Ho-Kuen;Lee, Jooyeoun
    • Journal of Digital Convergence
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    • v.18 no.6
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    • pp.53-63
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    • 2020
  • Electronic financial transactions are also actively increasing due to the rapid spread of information communication media such as the Internet, smart devices, and IoT, but as a derivative by-product, threats of financial security such as leakage of various personal information and hacking are also increasing. Therefore, the importance of financial security against this is increasing, but in Korea, financial security technology is relatively insufficient compared to advanced countries in the field of financial security, such as Active-X. Therefore, this study aims to present the major development direction in the domestic financial security field by comparing key technology trends with IPC classification frequency analysis, keyword frequency analysis, and keyword network analysis based on domestic and foreign financial security-related patent data. In conclusion, it seems that recent domestic and foreign trends have focused on the development of related technologies according to the development of smart device-based electronic financial services. Accordingly, it is intended to be used as the basis data for technology development of financial security by mapping the trend of financial security research trend and technology trend analysis through thesis data analysis that reflects the research of the preceding aspect as the technology of commercialization in the future.

Examining News Report Research Trends Using Keyword Network Analyses (국내 뉴스 보도 연구 동향에 관한 주제어 연결망 분석)

  • Cho, Yiyoung;Ahn, Dohyun
    • The Journal of the Korea Contents Association
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    • v.16 no.8
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    • pp.278-291
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    • 2016
  • This study examined research trends via network analyses of keywords appeared in academic research articles about news reports in South Korea during the last 10 years from 2006 to 2015. Keyword network analyses of 4410 keywords from 1108 articles suggested that framing, agenda setting, third-person effect, selective exposure, and uses and gratification were main theories but most studies used framing theory. Research areas included news reports on politics, economics, science, world issues, or tour. However, research on news reports covering culture, sports or daily life were not identified. In terms of media, research on both traditional and emerging media were ample. Research on broadcasting new, online news, and social media were frequently observed.

Research Trends in Journal of Fashion Business -A Social Network Analysis of Keywords in Fashion Marketing and Design Area- (키워드 네트워크 분석을 통한 「패션비즈니스」 연구 동향 -패션마케팅 및 디자인 분야를 중심으로-)

  • Lee, MiYoung;Lee, Jungmin
    • Journal of Fashion Business
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    • v.23 no.3
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    • pp.51-66
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    • 2019
  • The aim of this study is to identify research trends of "Journal of Fashion Business" by analyzing the keyword network of the paper published between 2006 and 2017. The papers selected for analysis in the study were 287 fashion design articles and 281 fashion marketing articles published between February 2006 and December 2017 and titles, volumes, publishing years, authors, keywords, and abstracts of each paper were collected for data analysis. The research was carried out through selection, collection of article data, keyword extraction and coding, keywords refinement, formation of network matrix, and analysis and visualization process. First, based on the title of the paper used in the analysis, the fashion design/aesthetics, marketing/social psychology, clothing materials, clothing composition, and other fields were classified. Research analysis used the Netminer 4 (Ver.4.3.2) program. Results indicated showed that the intellectual structure of the "Fashion Business" research paper showed key word changes over time, and the degree centrality and between centrality of the keywords.

Keyword trends analysis related to the aviation industry during the Covid-19 period using text mining (텍스트마이닝을 활용한 Covid-19 기간 동안의 항공산업 관련 키워드 트렌드 분석)

  • Choi, Donghyun;Song, Bomi;Park, Dahyeon;Lee, Sungwoo
    • 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.

Research Trend on Internet of Things and Smart City Using Keyword Fequency and Centrality Analysis : Focusing on United States, Japan, South Korea (키워드 빈도와 중심성 분석을 이용한 사물인터넷 및 스마트 시티 연구 동향: 미국·일본·한국을 중심으로)

  • Lee, Taekkyeun
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.18 no.3
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    • pp.9-23
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    • 2022
  • This study aims to examine research trends on the Internet of Things and smart city based on papers from the United States, Japan, and Korea. We collected 7113 papers related to the Internet of Things and smart city published from 2016 to 2021 in Elsevier's Scopus. Keyword frequency and centrality analysis were performed based on the abstracts of the collected papers. We found keywords with high frequency of appearance by calculating keyword frequency and identified central research keywords through the centrality analysis by country. As a result of the analysis, research on security, machine learning, and edge computing related to the Internet of Things and smart city were the most central and highly mediating research conducted in each country. As an implication, studies related to deep learning, cybersecurity, and edge computing in Korea have lower degree centrality and betweenness centrality compared to the United States and Japan. To solve the problem it is necessary to combine these studies with various fields. The future research direction is to analyze research trends on the Internet of Things and smart city in various regions such as Europe and China.

Cancer Research Trends in Traditional Korean Medical Journals since 2000 - Topic Modeling Using Latent Dirichlet Allocation and Keyword Network Analysis (2000년 이후 국내 한의학 암 관련 연구 동향 분석 - Latent Dirichlet Allocation 기반 토픽 모델링 및 연관어 네트워크 분석)

  • Kyeore Bae
    • The Journal of Internal Korean Medicine
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    • v.43 no.6
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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.

The Effects of City's Search Keyword Type on Facebook Page Fans and Inbound Tourists : Focusing on Seoul City (도시의 검색키워드 유형이 페이스북 페이지 팬 수 및 관광객 수에 미치는 영향에 관한 연구: 서울시를 중심으로)

  • Choi, Jee-Hye;Lee, Hyo-Bok
    • Journal of Digital Convergence
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    • v.15 no.10
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    • pp.93-101
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    • 2017
  • This study investigate the effect of each type of search volume on the number of Facebook fans and the number of tourists. According to the hierarchy effect model, the effect of communication appears to be the sequentiality of cognition-attitude-behavior. Applying this theory, this study predicted that when consumers who have higher involvement and knowledge on specific cities through search behavior, they will be more active in information search through Facebook fan page subscription and will lead to direct tourism behavior. To verify the prediction, we examined the influences among search volume of Seoul shown in Google Trend, the number of fans of official facebook page named 'Seoul Korea', and the number of foreign tourists. As a result, the type of search keyword was divided into four categories: tourism attraction keyword, natural environment keyword, symbolic keyword, and accessibility keyword. The regression analysis showed that tourism attraction keyword and symbolic keyword have influence on Facebook fanpage 'Like'. In addition, facebook fanpage fan size have mediation effect between search volume and number of tourists. All in all, it would be useful to appeal to foreign tourists with a message that emphasizes tourism attraction and Korea-related contents.

Research Trend Analysis for Sustainable QR code use - Focus on Big Data Analysis

  • Lee, Eunji;Jang, Jikyung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.9
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    • pp.3221-3242
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    • 2021
  • The purpose of the study is to examine the current study trend of 'QR code' and suggest a direction for the future study of big data analysis: (1) Background: study trend of 'QR code' and analysis of the text by subject field and year; (2) Methodology: data scraping and collection, EXCEL summary, and preprocess and big data analysis by R x 64 4.0.2 program package; (3) the findings: first, the trend showed a continuous increase in 'QR code' studies in general and the findings were applied in various fields. Second, the analysis of frequent keywords showed somewhat different results by subject field and year, but the overall results were similar. Third, the visualization of the frequent keywords also showed similar results as that of frequent keyword analysis; and (4) the conclusions: in general, 'QR code' studies are used in various fields, and the trend is likely to increase in the future as well. And the findings of this study are a reflection that 'QR code' is an aspect of our social and cultural phenomena, so that it is necessary to think that 'QR code' is a tool and an application of information. An expansion of the scope of the analysis is expected to show us more meaningful indications on 'QR code' study trends and development potential.

A Keyword analysis on the RFID research papers (RFID 연구 논문에 대한 주제어 분석)

  • Yang, Byoung-Hak
    • Journal of the Korea Safety Management & Science
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    • v.14 no.3
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    • pp.221-227
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    • 2012
  • This research is a key words analysis on Radio Frequency Identification. Key words were collected from Korean research papers in the electronic library DBpia. 700 papers published from 2001 to 2011 were included. The number of collected key words is 1460. The trend of publishing research papers was increased rapidly from 2005, reached peak at 2009 and decreased after 2010. Majority of key words were related to hardware, information technology and standardization. Selected 128 key words were analyzed and clustered by social network analysis to find a relationship among key words on RFID.