• Title/Summary/Keyword: Related Keywords

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Concept-based Compound Keyword Extraction (개념기반 복합키워드 추출방법)

  • Lee, Sangkon;Lee, Taehun
    • The Journal of Korean Association of Computer Education
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    • v.6 no.2
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    • pp.23-31
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    • 2003
  • In general, people use a key word or a phrase as the name of field or subject word in document. This paper has focused on keyword extraction. First of all, we investigate that an author suggests keywords that are not occurred as contents words in literature, and present generation rules to combine compound keywords based on concept of lexical information. Moreover, we present a new importance measurement to avoid useless keywords that are not related to documents' contents. To verify the validity of extraction result, we collect titles and abstracts from research papers about natural language and/or voice processing studies, and obtain the 96% precision in a top rank of extraction result.

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Knowledge Structure of the Korean Journal of Occupational Health Nursing through Network Analysis (네트워크분석을 통한 직업건강간호학회지 논문의 지식구조 분석)

  • Kwon, Sun Young;Park, Eun Jung
    • Korean Journal of Occupational Health Nursing
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    • v.24 no.2
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    • pp.76-85
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    • 2015
  • Purpose: The purpose of this study was to identify knowledge structure of the Korean Journal of Occupational Health Nursing from 1991 to 2014. Methods: 400 articles between 1991 and 2014 were collected. 1,369 keywords as noun phrases were extracted from articles and standardized for analysis. Co-occurrence matrix was generated via a cosine similarity measure, then the network was analyzed and visualized using PFNet. Also NodeXL was applied to visualize intellectual interchanges among keywords. Results: According to the results of the content analysis and the cluster analysis of author keywords from the Korean Journal of Occupational Health Nursing articles, 7 most important research topics of the journal were 'Workers & Work-related Health Problem', 'Recognition & Preventive Health Behaviors', 'Health Promotion & Quality of Life', 'Occupational Health Nursing & Management', 'Clinical Nursing Environment', 'Caregivers and Social Support', and 'Job Satisfaction, Stress & Performance'. Newly emerging topics for 4-year period units were observed as research trends. Conclusion: Through this study, the knowledge structure of the Korean Journal of Occupational Health Nursing was identified. The network analysis of this study will be useful for identifying the knowledge structure as well as finding general view and current research trends. Furthermore, The results of this study could be utilized to seek the research direction in the Korean Journal of Occupational Health Nursing.

Identifying Topics of LIS Curricula by Keyword Analysis - Focused on Information Technology Classes of US and Korea (교과 키워드 분석을 통한 문헌정보학과 교육 주제 연구 - 한국·미국 정보기술관련 교과 중심으로 -)

  • Choi, Sanghee
    • Journal of Korean Library and Information Science Society
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    • v.50 no.2
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    • pp.43-60
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    • 2019
  • Since information technology such as database or network technology was brought into the information and library science fields, the functions and services of libraries have drastically changed. To cope with the changes of fields, library schools have been improving curricula. This study collected curricula of library and information science in US and Korea and selected classes related to information technology. It also investigated the title keywords and keywords of class description statistically. As a result, 'system, 'database', 'network', 'programing', 'web' are major topic keywords for both countries, but 'library'shows high frequency pnly in Korea.

A Study on Keyword Information Characteristics of Product Names for Online Sales of Women's Jeans Using Text Mining (텍스트마이닝을 활용한 온라인 판매 여성 청바지 상품명에 나타난 키워드의 정보 특성 분석)

  • Yeo Sun Kang
    • Journal of the Korean Society of Clothing and Textiles
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    • v.47 no.1
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    • pp.35-51
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    • 2023
  • This study used text mining to extract 2,842 keywords from 7,397 product names and organized them into categories in order to analyze the characteristics of keywords appearing in the product names of jeans after 2020. The item category included denim and Chungbaji [청바지], and Ilja [일자], while the silhouette category included wide and bootcut. In addition, high-waist and banding comprised the making sector, and the materials category consisted of napping, spandex, and soft blue. Denim surpassed the others in frequency, co-occurrence frequency, and centrality, and co-appeared with various other keywords. Also, the co-appearance of item and silhouette was prominent, and there were many keyword combinations that showed characteristics related to (a) high waist; (b) hemline detail; (c) rubber band; and (d) partial tearing. Furthermore, idiom expressions such as 'slim fit' and 'back tearing', which were not highlighted in the co-occurrence frequency, were additionally confirmed through correlation. Therefore, the product name analysis effectively identified the detailed characteristics of the silhouette and the making of jeans preferred by consumers.

Research trends in the Korean Journal of Women Health Nursing from 2011 to 2021: a quantitative content analysis

  • Ju-Hee Nho;Sookkyoung Park
    • Women's Health Nursing
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    • v.29 no.2
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    • pp.128-136
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    • 2023
  • Purpose: Topic modeling is a text mining technique that extracts concepts from textual data and uncovers semantic structures and potential knowledge frameworks within context. This study aimed to identify major keywords and network structures for each major topic to discern research trends in women's health nursing published in the Korean Journal of Women Health Nursing (KJWHN) using text network analysis and topic modeling. Methods: The study targeted papers with English abstracts among 373 articles published in KJWHN from January 2011 to December 2021. Text network analysis and topic modeling were employed, and the analysis consisted of five steps: (1) data collection, (2) word extraction and refinement, (3) extraction of keywords and creation of networks, (4) network centrality analysis and key topic selection, and (5) topic modeling. Results: Six major keywords, each corresponding to a topic, were extracted through topic modeling analysis: "gynecologic neoplasms," "menopausal health," "health behavior," "infertility," "women's health in transition," and "nursing education for women." Conclusion: The latent topics from the target studies primarily focused on the health of women across all age groups. Research related to women's health is evolving with changing times and warrants further progress in the future. Future research on women's health nursing should explore various topics that reflect changes in social trends, and research methods should be diversified accordingly.

Network, Centrality, and Topic Analysis on Korea's Trade and Economy with Latin America and the Caribbean Area (한국의 중남미 지역연구 네트워크와 중심성 및 무역과 경제에 대한 토픽 변동분석)

  • Chae-Deug Yi
    • Korea Trade Review
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    • v.47 no.6
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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.

Systematic Review of Research Progress on Borderline Resectable Pancreatic Cancer: A Bibliometric and Visualized Analysis (경계성 절제가능형 췌장 연구 동향에 대한 체계적인 문헌 고찰: 계량서지학적 분석 및 시각화된 분석)

  • Jae Keun Park;Ji Woong Hwang
    • Journal of Digestive Cancer Research
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    • v.12 no.1
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    • pp.23-30
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    • 2024
  • Borderline resectable pancreatic cancer, an intermediate stage between a completely resectable state and an unresectable state, requires a multidisciplinary treatment approach. This study aimed to elucidate the main characteristics and recent research trends regarding borderline resectable pancreatic cancer to gain further insights into them. Data from published papers about borderline resectable pancreatic cancer were collected from Web of Science (2014-2023) for the analysis. This study included 355 papers; data on major countries, publishing organizations, and keywords were collected and analyzed. Furthermore, R studio and VOSviewer were used for the qualitative and quantitative analyses of keywords. Publication of papers on borderline resectable pancreatic cancer was observed to be increasing annually by 12.8%, with the United States and Japan being the main publishing countries. In 2014, keywords related to surgery and chemotherapy were dominant; however, a shift toward more integrative approaches, such as neoadjuvant therapy, was observed over time. This study demonstrates rapidly evolving trends and paradigm changes in the research and management of borderline resectable pancreatic cancer. Thus, the results of this study are expected to contribute to establishing future research strategies and improving patient treatment outcomes.

Research Trend on Digital Twin Based on Keyword Frequency and Centrality Analysis : Focusing on Germany, the United States, Korea (키워드 빈도 및 중심성 분석에 기반한 디지털 트윈 연구 동향 : 독일·미국·한국을 중심으로)

  • Lee Taekkyeun
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.20 no.2
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    • pp.11-25
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    • 2024
  • This study aims to analyze research trends in digital twin focusing on Germany, the US, and Korea. In Elsevier's Scopus, we collected 4,657 papers about digital twin published in from 2019 to 2023. Keyword frequency and centrality analysis were conducted on the abstracts of the collected papers. Through the obtained keyword frequencies, we tried to identify keywords with high frequency of occurrence and through centrality analysis, we tried to identify central research keywords for each country. In each country, 'digital_twin', 'machine_learning', and 'iot' appeared as research keywords with the highest interest. As a result of the centrality analysis, research on digital twin, simulation, cyber physical system, Internet of Things, artificial intelligence, and smart manufacturing was conducted as research with high centrality in each country. The implication for Korea is that research on virtual reality, digital transformation, reinforcement learning, industrial Internet of Things, robotics, and data analysis appears to have been conducted with low centrality, and intensive research in related areas appears to be necessary.

Landscape Characteristics of Youngnam-Lu through the Analysis of Poetry (시문분석을 통한 영남루의 경관 특징에 관한 연구)

  • Ahn, Gye-Bog
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.32 no.1
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    • pp.1-9
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    • 2014
  • The purpose of this study was to identify the landscape characteristics of Youngnam-Lu by performing text analysis of related Korean poems over 600 years. A total of 354 poems were quantitatively analyzed for keywords and terms in particular categories such as nature. As a subsidiary analysis, topographic map was examined using CAD along with analysis of antique maps. Of the 354 poems reviewed, keywords frequently used are: 'Scenic sites'- 56 times, 'Long river' (長江) and 'Long stretched forest'(長林) - 39 times each, 'Superb scenery'- 31 times, 'Large field scenery'- 19 times, and 'Thousand-layered mountain view' - 14 times. In total, these keywords occurred 159 times in 44.9 % of these poems.1) The words used frequently in these poems, especially for those fall under category of nature, can be scored into different subcategories such as natural phenomena and geographical features. Occurrences of terms in each subcategory were main criteria for the analysis and the following is a list of subcategories with frequency in descending order: Natural phenomena (44%), geographical features (33%), plants (14%), and animals (9%). Among natural phenomena, phenomena related to sky were most frequent, 41 times, which might be due to superb sky view from Youngnam-Lu. Also geographical features of Youngnam-Lu were reflected in these poems, and the most prominent features were 'flow of the river' and 'Sand island' located in the Milyang River. These poems contained fairly large number of terms related to musical instruments (8%) which suggest that Young-Nam-Lu as a place where various musical instruments performances were held.

Analysis of interest in implant using a big data: A web-based study (빅 데이터를 이용한 임플란트에 대한 관심도 분석: 웹 기반 연구)

  • Kong, Hyun-Jun
    • The Journal of Korean Academy of Prosthodontics
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    • v.59 no.2
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    • pp.164-172
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    • 2021
  • Purpose: The purpose of this study was to analyze the level of interest that common Internet users have in dental implant using a Google Trends, and to compare the level of interest with big data from National Health Insurance Service. Materials and methods: Google Trends provides a relative search volume for search keywords, which is the average data that visualizes the frequency of searches for those keywords over a specific period of time. Implant was selected as the search keyword to evaluate changes in time flows of general Internet users' interest from 2015 to 2019 with trend line and 6 month moving average. Relative search volume for implant was analyzed with the number of patients who received National Health Insurance coverage for implant. Interest in implant and conventional denture was compared and popular related search keywords were analyzed. Results: Relative search volume for implant has increased gradually and showed a significant positive correlation with the total number of patients (P<.01). Interest in implant was higher than denture for most of the time. Keywords related to implant cost were most frequently observed in all years and related search on implant procedure was increasing. Conclusion: Within the limitations of this study, the public interest in dental implant was gradually increasing and specific areas of interest were changing. Web-based Google Trends data was also compared with traditional data and significant correlation was confirmed.