• Journal of Korean society of Dental Hygiene
• /
• v.21 no.5
• /
• pp.639-644
• /
• 2021

Objectives: The purpose of this study was to analyze the factors that affected the number of citations for articles published in the Journal of Korean Society of Dental Hygiene based on previous studies. Methods: Information on papers including the number of citations was collected using a web crawling technique. The effect of the number of author keywords, the number of Medical Subject Headings (MeSH) keywords, MeSH match rate, abstract word count and keyword-abstract ratio on the number of citations was analyzed by multiple regression analysis. Results: The use of the MeSH keyword did not have a significant effect on the number of citations. Among the other factors, only the keyword-abstract ratio was statistically significant. Conclusions: Select a topic of constant interest in the field, write the title in detail using colons or asterisks if necessary, and do not repeat the words used in the title in keywords. Select specific keywords deeply related to the topic. In particular, choice words or phrases that are frequently used in the abstract. If the MeSH keyword selection contradicts the previous strategies, boldly give up the MeSH keyword.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.1
• /
• pp.141-146
• /
• 2018

The authors' author keywords are the most important elements that characterize the contents of the paper, By analyzing this in real time and providing it to users, It is possible to grasp research trends. Unstructured data of a journal created in a paper is constructed as a database, make use of this to make index data structure that can search in real time. In the index data structure, a thesis containing a specific keyword is searched, By extracting and clustering the author keywords, By presenting to the user a word cloud that can be displayed by size according to the weight, designed a method to visualize research trends. We also present the results of the research trend analysis of the keywords "virus" and "iris recognition" in the implemented system.

• Journal of the Korean Society for information Management
• /
• v.39 no.1
• /
• pp.309-330
• /
• 2022

Intellectual structure analysis, which quantitatively identifies the structure, characteristics, and sub-domains of fields, has rapidly increased in recent years. Analysis techniques traditionally used to conduct intellectual structure analysis research include bibliographic coupling analysis, co-citation analysis, co-occurrence analysis, and author bibliographic coupling analysis. This study proposes a novel intellectual structure analysis method, Keyword Bibliographic Coupling Analysis (KBCA). The Keyword Bibliographic Coupling Analysis (KBCA) is a variation of the author bibliographic coupling analysis, which targets keywords instead of authors. It calculates the number of references shared by two keywords to the degree of coupling between the two keywords. A set of 1,366 articles in the field of 'Open Data' searched in the Web of Science were collected using the proposed KBCA technique. A total of 63 keywords that appeared more than 7 times, extracted from 1,366 article sets, were selected as core keywords in the open data field. The intellectual structure presented by the KBCA technique with 63 key keywords identified the main areas of open government and open science and 10 sub-areas. On the other hand, the intellectual structure network of co-occurrence word analysis was found to be insufficient in the overall structure and detailed domain structure. This result can be considered because the KBCA sufficiently measures the relationship between keywords using the degree of bibliographic coupling.

• Journal of Korean Library and Information Science Society
• /
• v.45 no.1
• /
• pp.149-171
• /
• 2014

This study makes some suggestions to cluster works from the search result of library databases. Specifically, the author suggests modifying the current practices and rules of KORMARC 24X field based on intent of RDA, which is the new cataloging standard. After identifying some problems in entering bibliographic data into 24X field, the author proposes solutions to such problems. The solutions include improvements in (1) Goanje description (관제기술), (2) use of uniform title, and (3) processing of marks, etc. The study demonstrates that users can conduct a fronted keyword searching effectively and identify the relevant bibliographic records easily from the clustered search results.

• Journal of Information Science Theory and Practice
• /
• v.9 no.3
• /
• pp.76-106
• /
• 2021

The study analyzed bibliometric data of papers published in Korea Citation Index (KCI) and Web of Science (WoS) journals from 2002 to 2021. After examining size differences of KCI and WoS domains in the number of authors, institutions, and journals to put publication and citations counts in perspective, the study investigated co-authorship patterns over time to compare collaboration trends of Korean and international scholars and analyzed the data at author, institution, and journal levels to explore how the influences of authors, institutions, and journals on research output differ across domains. The study also conducted frequency-based analysis of keywords to identify key topics and visualized keyword clusters to examine topic trends. The result showed Korean LIS authors to be twice as productive as international authors but much less impactful and Korean institutions to be at comparable levels of productivity and impact in contrast to much of productivity and impact concentrated in top international institutions. Citations to journals exhibited initially increasing pattern followed by a decreasing trend though WoS journals showed far more variance than KCI journals. Co-authorship trends were much more pronounced among international publication, where larger collaboration groups suggested multi-disciplinary and complex nature of international LIS research. Keyword analysis found continuing diversification of topics in international research compared to relatively static topic trend in Korea. Keyword visualization showed WoS keyword clusters to be much denser and diverse than KCI clusters. In addition, key keyword clusters of WoS were quite different from each other unlike KCI clusters which were similar.

• Journal of Society of Preventive Korean Medicine
• /
• v.25 no.2
• /
• pp.33-43
• /
• 2021

Objectives : This study seeks to grasp the current status of Koryo medical research in North Korea, by focusing on researchers and research topics. Methods : A network analysis of co-authors and keyword which were extracted from Koryo Medicine - a North Korean traditional medicine journal, was conducted. Results : The results of author network analysis was a sparse network due to the low correlation between authors. The domain-wide network density of co-authors was 0.001, with a diameter of 14, average distance between nodes 4.029, and average binding coefficient 0.029. The results of the keyword network analysis showed the keyword "traditional medicine" had the strongest correlation weight of 228. Other keywords with high correlation weight was common acupuncture (84) and intradermal acupuncture(80). Conclusions : Although the co-authors of the Koryo Medicine did not have a high correlation with each other, they were able to identify key researchers considered important for each major sub-network. In addition, the keywords of the Koryo Medicine journals had a very high linkage to herbal medicines.

• Journal of Korean Medicine Rehabilitation
• /
• v.34 no.1
• /
• pp.49-64
• /
• 2024

Objectives By bibliographically analyzing acupuncture treatment studies for temporomandibular disorders over the past 20 years, we found an overview of global trends and a new perspective on future research directions. Methods We searched on the Web of Science webpage through the formula (TS=[temporomandibular] OR TS=[craniomandibular] OR TS=[jaw]) AND (TS=[^*acupuncture] OR TS=[dry needl^*] OR TS=[warm needl^*] OR TS=[thread embed^*]) AND (PY=[2003-2022]). And it was analyzed by year, research field, academic journal, country, research institute, author, and keyword. Results 194 papers were searched, and 92 papers were finally selected. The number of papers published over the past 20 years has been on the rise. Research has been the most active in the field of Dentistry Oral Surgery Medicine. Brazil published the most papers. And by institution, Universidade de Sao Paulo published the most papers. Among the authors, Fernández-de-las-Peñas has published the most papers. In the analysis by keyword, the top five keywords were temporomandibular joint disorder, acupuncture, myofascial pain, pain and management. Conclusions This study will provide useful guidelines for setting the direction of research by referring to the research status and keyword analysis when conducting research on the acupuncture on temporomandibular disorder in the future.

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.06c
• /
• pp.385-389
• /
• 2010

논문에 부여되는 저자 주제어(author keyword)는 논문을 분류 및 검색하는데 활용될 수 있다. 이렇게 주제어를 부여할 때 자동으로 저자 주제어를 추천한다면 사용자에게 편리성을 제공하고 저자가 직접 부여한 저자 주제어 이외에 추가적으로 주제어가 있는지도 확인할 수 있어 유용하다. 본 연구에서는 논문에 달려있는 다수의 주제어 중 하나의 주제어를 선별하여 Labeled LDA를 이용해 주제어와 초록(abstract)의 관계를 학습했다. 이후 초록이 주어지면 자동으로 저자 주제어를 부여할 수 있도록 추천하는 기법을 제안하고 그에 따른 실험을 진행했다. 본 논문에서는 실험을 통하여 기계학습을 이용한 저자 주제어의 추천이 어느 정도의 성능을 보이는지 평가하고 향후 연구의 방향을 제시한다.

• Journal of Information Technology Services
• /
• v.17 no.2
• /
• pp.143-163
• /
• 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.

• International Journal of Knowledge Content Development & Technology
• /
• v.2 no.2
• /
• pp.17-29
• /
• 2012

All academic information on the web or elsewhere has its creator, that is, a subject who has created the information. The subject can be an individual, a group, or an institution, and can be a nation depending on the nature of the relevant information. Most information is composed of a title, an author, and contents. An essay which is under the academic information category has metadata including a title, an author, keyword, abstract, data about publication, place of publication, ISSN, and the like. A patent has metadata including the title, an applicant, an inventor, an attorney, IPC, number of application, and claims of the invention. Most web-based academic information services enable users to search the information by processing the meta-information. An important element is to search information by using the author field which corresponds to a personal name. This study suggests a method of efficient indexing and using the adjacent operation result ranking algorithm to which phrase search-based boosting elements are applied, and thus improving the accuracy of the search results of personal names. It also describes a method for providing the results of searching co-authors and related researchers in searching personal names. This method can be effectively applied to providing accurate and additional search results in the academic information services.