• 한국산업정보학회논문지
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• 제25권1호
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• pp.41-53
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• 2020

공급사슬관리는 기업 경영의 핵심 성공요소 중 하나가 되었다. 이에 따라서 많은 연구자들이 지속적으로 공급사슬관리와 관련한 연구를 진행하였다. 본 연구에서는 지난 10년 동안 국내 학술지에 발표한 공급사슬관리 분야 연구논문을 대상으로 네트워크 텍스트 분석 방법으로 연구 동향을 분석하였다. RISS 학술 데이터 베이스에서 총 586편의 관련 논문을 검색하여 개별 연구논문의 키워드 노드를 중심으로 키워드 네트워크를 구축하여 네트워크 분석을 시행하였다. 분석결과에 따르면 지난 10년 동안 국내 공급사슬관리 연구는 물류, 정보시스템, 파트너십, 위험관리, 지속가능 분야를 중심으로 연구되었음을 확인할 수 있었다.

• 수산해양교육연구
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• 제26권1호
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• pp.156-165
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• 2014

The purpose of this study was to find research trends of smart learning. For this, we identified the research's characteristics such as the subject or keyword of research, method, data collection, and statistical analysis method. The 2,865 articles published from 1995 to 2013 were gathered from five Korean academic journals related to smart learning. Among them, research keyword, areas, research method, data collection method, and statistical analysis method were analyzed on 596 papers. The findings of this study were as follows: (a) Smart learning papers such keyword likes u-learning, m-learning, and smart-learning were emerging after 2006. Smart learning papers with ICT related topics were highly increased after 2000, but they were decreased after 2006. Smart learning papers with e-learning related keywords were steadily increased after 2000 through 2013. (b) The research field of deign had the highest portion in smart learning research, but managing had the lowest portion. (c) Development was mainly used as a research method. Both questionnaire and experiment were mainly used for collecting data methods. T-test and frequency analysis were mainly used as statistical analysis methods.

• Journal of Korea Trade
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• 제24권5호
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• pp.71-86
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• 2020

Purpose - This study investigates research trends by searching for English keywords and abstracts in 1,511 Korean journal articles in the Korea Citation Index from the 2002-2019 period using the term "Port." The study aims to lay the foundation for a more balanced development of port research. Design/methodology - Using abstract and keyword data, we perform frequency analysis and word embedding (Word2vec). A t-SNE plot shows the main keywords extracted using the TextRank algorithm. To analyze which words were used in what context in our two nine-year subperiods (2002-2010 and 2010-2019), we use Scattertext and scaled F-scores. Findings - First, during the 18-year study period, port research has developed through the convergence of diverse academic fields, covering 102 subject areas and 219 journals. Second, our frequency analysis of 4,431 keywords in 1,511 papers shows that the words "Port" (60 times), "Port Competitiveness" (33 times), and "Port Authority" (29 times), among others, are attractive to most researchers. Third, a word embedding analysis identifies the words highly correlated with the top eight keywords and visually shows four different subject clusters in a t-SNE plot. Fourth, we use Scattertext to compare words used in the two research sub-periods. Originality/value - This study is the first to apply abstract and keyword analysis and various text mining techniques to Korean journal articles in port research and thus has important implications. Further in-depth studies should collect a greater variety of textual data and analyze and compare port studies from different countries.

• 디지털산업정보학회논문지
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• 제18권3호
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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.

• International journal of advanced smart convergence
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• 제11권2호
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• pp.95-101
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• 2022

The development of the 4th industry has increased social media, and the rise of COVID-19 has stimulated non-face-to-face services. People's consumption patterns are also changing a lot due to non-face-to-face services. In this paper, food content keywords are derived through social network-based semantic network analysis, emotions are analyzed, and keywords applied to food recommendation platforms are input. We collected food, influencer, and corona keyword analysis data through Textom. A lot of research has been done through online reviews of existing influencer content. However, there is a lack of research on keyword sentiment analysis provided by influencers rather than consumers and research perspectives. This paper uploads language and topics derived through online reviews of existing publications and subscribers, and goes beyond the limits used in marketing methods. By analyzing keywords that influencers suggest when uploading content, you can apply data that applies them to food recommendation platforms and applications.

• 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.

• 정보처리학회논문지D
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• 제19D권4호
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• pp.263-270
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• 2012

최근 초고속 인터넷과 대용량 데이터베이스 기술의 발전으로 웹 문서의 양이 크게 증가하였으며, 이를 효과적으로 관리하기 위하여 문서의 주제별 자동 분류가 중요한 문제로 대두되고 있다. 본 연구에서는 한글 형태소 및 키워드 분석에 기초한 문서 특성 추출 방법을 제안하고, 이를 이용하여 웹 문서와 같은 비구조적 문서의 주제를 예측하여 문서를 자동으로 분류하는 방법을 제시한다. 먼저, 문서 특성 추출을 위하여 한글 형태소 분석기를 사용하여 용어를 선별하고, 각 용어의 빈도와 주제 분별력을 기초로 주제 분별 용어인 키워드 집합을 생성한 후, 각 키워드에 대하여 주제 분별력에 따라 점수화한다. 다음으로, 추출된 문서 특성을 기초로 상용 소프트웨어를 사용하여 의사 결정 트리, 신경망 및 SVM의 세 가지 분류 모델을 생성하였다. 실험 결과, 제안한 특성 추출 방법을 이용한 문서 분류는 의사 결정 트리 모델의 경우 평균 Precision 0.90 및 Recall 0.84 로 상당한 정도의 분류 성능을 보여 주었다.

• 한국IT서비스학회지
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• 제17권2호
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• pp.143-163
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• 2018

The business models has a great impact on the successful management of enterprises. Business environment has been shifting from industrial economy to knowledge-based economy. Enterprises go through numerous trials for successful management in the changing environment. Along with trial tests, research areas have been growing simultaneously. Although many researches have been conducted with regard to business models, it is very insufficient to systematically analyze the knowledge flow of research. Accordingly, successive researchers who want to study the business model may find it difficult to establish the orientation of future application research based on understanding the process of changing the knowledge structure that have accumulated so far. This study is intended to determine the current state of the business model research and to understand the process of knowledge structure changes in keywords that appear in 2,667 business model articles in the SCOPUS database. Identifying the knowledge structure has been completed through social network analysis, a methodology based on the 'relationship', and the changes in the knowledge structure were identified by classifying them into four different periods. The analysis showed that, first, the number of business model co-author increases over time with the need for academic diversity. Second, the 'innovation' keyword has the biggest center in the network, and over time, the lower-rank keyword which was in the former period has emerged as the top-rank keyword. Third, the cohesiveness group decreased from 12 before 2000 to 5 in 2015 and also the modularity decreased as well. Finally, examining characteristics of study area through a cognitive map showed that the relationships between domains increased gradually over time. The study has provided a systematic basis for understanding the current state of the business model research and the process of changing knowledge structure. In addition, considering that no research has ever systematically analyzed the knowledge structure accumulated by individual researches, it is considered as a significant study.

• 한국문헌정보학회지
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• 제50권3호
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• pp.383-402
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• 2016

본 연구의 목적은 도서관마케팅 관련 국내외 연구의 저자 키워드 네트워크 분석을 통해 도서관마케팅연구의 경향성을 살펴보고 국외 연구와의 비교를 통해 국내 연구가 지니는 특성을 살펴보는데 있다. 분석 대상은 국내의 경우 문헌정보학분야 4대 학회지의 도서관마케팅 관련 연구의 저자 키워드이며 국외의 경우 Scopus데이터베이스에 수록되어 있는 문헌정보학분야의 도서관마케팅 관련 연구의 저자 키워드이다. 수집된 저자 키워드는 NetMiner4 소프트웨어를 활용하여 분석하였다. 분석 결과 1) 국내의 도서관마케팅연구는 주로 공공도서관을 대상으로 한 반면 국외의 경우 대학도서관을 대상으로 한 연구가 상대적으로 많았다, 2) 국내의 경우, 도서관마케팅연구의 주제가 다양화되지 못한 경향이 있으며 일부 소수 학자들의 학문적 관심에 의해 주도되는 경향성이 강하였다, 3) 국외의 경우, 디지털시대에 걸맞은 소셜미디어와 온라인 등을 통한 마케팅적 접근이 활발한 반면 국내의 경우는 이에 대한 관심이 미미하였다, 4) 국내외의 경우 모두 학교도서관에 대한 도서관마케팅연구자들의 관심은 많지 않은 것으로 나타났다.

• 산업융합연구
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• 제18권2호
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• pp.45-50
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• 2020

이 연구는 교육과정 분야의 연구에서 중요하게 다루어지는 키워드와 그들의 관계를 살펴보기 위해 실시되었다. 연구를 위해 2002년부터 2019년까지 게재된 644편의 교육과정 논문에서 1,935개의 키워드를 추출하여 분석하였다. 자료 분석 단계에서는 KrKwic와 KrTitle 프로그램을 통해 키워드를 추출한 후 1-mode network matrix를 작성하였고, UCINET 6과 NetDraw 프로그램을 활용하여 네트워크 분석과 시각화 작업을 수행하였다. 연구 결과는 다음과 같다. 첫째, 전체 키워드 출현 빈도 분석 결과, 교육과정이 가장 많이 출현하였으며, 다음은 교육과정 개발, 국가 교육과정, 역량기반 교육과정, 2015 개정 교육과정, 교육과정 실행, 이해중심 교육과정, 교사 교육, 학교 교육과정, IBDP 등의 순으로 나타났다. 둘째, 연결 중심성 분석 결과에 따르면, 교육과정 개발이 가장 높게 나타났다. 이와 함께 교육과정, 역량기반 교육과정, 국가 교육과정, 2015 개정 교육과정, 이해중심 교육과정, 역량, 핵심 역량, 고등학교 교육과정, 교과서, 교육과정 실행, 교사 교육, IBDP 등의 순서로 높게 나타났다.