• Journal of The Korean Dental Society of Anesthesiology
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• 제14권3호
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• pp.143-149
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• 2014

Background: The purpose of this study was to analyze the equality between key words used in the Journal of Korean Dental Society of Anesthesiology and Medical Subject Headings (MeSH). Methods: A total of 666 English key words in 187 papers (average 3.5 words in a paper) from 2001 to 2014 were eligible for this study. We classified them according to matched, and non-matched terms. After descriptive analysis, we assayed patterns of errors in using MeSH, and reviewed frequently used non-MeSH terms. Results: Fifty nine point six percent (59.6%) of total key words were completely coincident with MeSH terms, 40.39% were not MeSH terms. Conclusions: The results show that the coincidence rate of key words with MeSH terms was at a moderate level. However, there is a need for us to understand MeSH more specifically and accurately. Use of proper key words aligned with the international standards such as MeSH is important to be properly cited. The authors should pay attention and be educated on correct use of MeSH as key words.

• Journal of the Korean Society of Physical Medicine
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• 제7권3호
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• pp.367-377
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• 2012

Purpose : The purpose of this study was to investigate the coincidence between keywords of Journal of the Korean Society of Physical Medicine (JKSPM) and MeSH terms, a controlled vocabulary used in MEDLINE. Methods : A total of 838 keywords used in 252 papers of JKSPM from Vol.1, No.1, 2006 to Vol.7, No.1, 2012 were compared with MeSH terms. All of keywords are classified to three large categories; complete coincidence, incomplete coincidence, and complete incoincidence. Results : The keywords in complete coincidence category were 183(21.8%), the keywords in incomplete coincidence category were 378(45.1%), and the keywords in complete incoincidence category were 277(33%). The most used keyword in complete coincidence category was 'stroke' and in complete incoincidence category was 'balance'. The most used keyword matching entry terms in incomplete coincidence category was 'elderly'. Conclusion : The rate of complete coincidene of keywords with MeSH terms was not higher than the rates of incomplete coincidence and complete incoincidence. It is necessary to understand MeSH terms more accurately and specifically. The JKSPM should ask the authors to use MeSH terms as keyword when they submit the paper.

• Journal of Korean society of Dental Hygiene
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• 제18권6호
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• pp.1047-1055
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• 2018

Objectives: The purpose of this study was to compare the author key words and MeSH (Medical Subject Headings) terms in the Journal of Korean Society of Dental Hygiene (JKSDH). Methods: A total of 3,242 author key words from 974 informative articles published from 2001 to 2015 were compared with MeSH terms, according to the criteria of complete coincidence, incomplete coincidence, and complete non-coincidence. Results: The coincidence rate of 564 author key words with MeSH terms was 17.4%. The author key words that appeared most frequently (in descending order) were oral health (41 times), dental hygienists (30 times), dental caries (29 times), and knowledge (29 times). There was a non-coincidence rate of 70.5% for 2,286 author key words with MeSH terms. Conclusions: Many author key words used in the JKSDH did not coincide with MeSH terms. The use of author key words that coincide with MeSH terms is necessary to accomplish the international journal.

• Journal of Sasang Constitutional Medicine
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• 제25권1호
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• pp.34-42
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• 2013

Objectives The purpose of this study was analyzing the equality between the MeSH terms and the keyword used in the papers published in Journal of Sasang Constitutional Medicine and investigating how to use an appropriate MeSH terms as keyword in the papers. Methods A total of 704 keyword used in 177 papers published from 2009 to 2012 in Journal of Sasang Constitutional Medicine were analyzed to investigate the equality between the keyword and the MeSH terms. The collected data was analyzed using SPSS 17.0 software for frequency analysis. Results Among the 704 keyword, 107 keyword(15.2%) was perfectly matched with the MeSH terms. 64 keyword(9.1%) showed partial difference was with the MeSH terms, and 11 keyword(1.7%) showed partial difference was with the Entry terms. 127 keyword(18.0%) were included in the exception item due to the nature of journal, and 395 keyword(56.1%) were not perfectly matched with the MeSH terms. In the yearly analysis result, the number of papers that keyword and MeSH terms perfectly matched was not significant changed, however the number of papers that keyword and MeSH terms did not matched was continuously increased, which clearly indicate use of MeSH terms as the keyword of the papers published in the journal of Sasang constitution medicine is insufficient. Conclusions The papers published in journal of Sasang constitutional medicine need to be cited in various fields and the paper's finding need to affect in other studies for the development of Korean medicine and Sasang constitutional medicine. The use of proper keyword aligned with the international standards is necessary to accomplish the globalization of them.

• Proceedings of the Korean Information Science Society Conference
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• 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (B)
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• pp.383-385
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• 2003

본 논문에서는 개념 기반 검색엔진 시스템(Concept-based Search Engine System)의 검색 정확도를 향상시키기 위한 방법으로 MeSH를 이용하였다. MeSH는 Medical Subject Headings의 약자로서 MEDLINE 논문의 원활한 검색을 위하여 주제어를 코드화한 것으로 이를 개념 그래프의 시소러스로 사용하여 개념 그래프의 가장 중요한 부분인 개념 추출의 정확성을 보장하도록 하였다. 본 논문은 2003년 MeSH의 Descriptor Data의 Term 항목을 사용하여 개념과 관련이 있는 유의어를 추출했다. 추출된 유의어로 개념 그래프를 구성한 것과 문서 내에서의 단어 빈도수에 의하여 개념 그래프를 구성한 것의 검색 결과를 비교한 결과 MeSH 를 시소러스로 사용하여 개념 그래프를 구성한 것이 훨씬 더 정확한 결과를 내는 것을 확인할 수 있었다.

• Journal of Korean Academy of Nursing
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• 제35권7호
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• pp.1420-1425
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• 2005

Purpose: We try to disclose how much the keywords of the papers from the Journal of the Korean Academy of Nursing coincide with MeSH terminologies and to understand the major subjects of the recent nursing research in Korea from keywords. Methods: Keywords of journals were extracted and compared with MeSH terms. The frequency of the appearance of each keyword was sorted by a descending order. Results: Coincidence rate of 1,235 keywords with MeSH terms was $51.6\%$. Out of them, depression, elderly, stress, self efficacy, quality of life, exercise, middle-aged women, and women appeared most frequently in descending order. Conclusion: Coincidence rate of the keywords with MeSH terms was at an acceptable level, however to improve it, the education of submitters and editorial board members are required, as well as the copy editor, to take a role in checking keywords. To infer the subjects of the research from keywords might well represent the recent topics of research work.

• Journal of Korean Library and Information Science Society
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• 제52권1호
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• pp.79-108
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• 2021

Information retrieval in the health field has several challenges. Health information terminology is difficult for consumers (laypeople) to understand. Formulating a query with professional terms is not easy for consumers because health-related terms are more familiar to health professionals. If health terms related to a query are automatically added, it would help consumers to find relevant information. The proposed query expansion (QE) models show how to expand a query using MeSH terms. The documents were represented by MeSH terms (i.e. Bag-of-MeSH), found in the full-text articles. And then the MeSH terms were used to generate LDA (Latent Dirichlet Analysis) topic models. A query and the top k retrieved documents were used to find MeSH terms as topic words related to the query. LDA topic words were filtered by threshold values of topic probability (TP) and word probability (WP). Threshold values were effective in an LDA model with a specific number of topics to increase IR performance in terms of infAP (inferred Average Precision) and infNDCG (inferred Normalized Discounted Cumulative Gain), which are common IR metrics for large data collections with incomplete judgments. The top k words were chosen by the word score based on (TP *WP) and retrieved document ranking in an LDA model with specific thresholds. The QE model with specific thresholds for TP and WP showed improved mean infAP and infNDCG scores in an LDA model, comparing with the baseline result.

• Annual Conference on Human and Language Technology
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• 한국정보과학회언어공학연구회 2004년도 제16회 한글.언어.인지 한술대회
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• pp.82-89
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• 2004

본 논문에서는 한국어 의학 논문의 요약문으로부터 자동 영문 MeSH 키워드 제안 시스템을 소개하고, 띄어쓰기 변이(spacing variant) 문제를 해결할 수 있는 방법을 제안한다. 띄어쓰기 변이란 표준 한글 맞춤법에 비해 다르게 띄어쓰기된 것을 말한다. 이를 위해 시소러스에는 생성 가능한 모든 띄어쓰기 변이 대신에 최대 띄어쓰기 어구만을 저장하고, 문서에서 K-MeSH 용어를 찾기 위해 음절단위 부분문자열 검색을 사용한다. 이 방법으로 한국어 의학 논문의 요약문에서 K-MeSH 용어를 추출한 후, TF-IDF 순위 함수를 이용하여 상위 10위내의 키워드를 저자가 선정한 영문 키워드와 비교한 결과 58%가 일치하였다. 이는 기존 방법에 비해 42%정도의 시소러스 크기가 축소되었고, 상위 10위내에서 영문 MeSH 키워드 추천 재현률이 약 7.8% 증가한 것으로 효과적인 방법임을 보여주었다.

• Journal of Korean society of Dental Hygiene
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• 제19권6호
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• pp.1059-1066
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• 2019

Objectives: This study aimed to identify authors' key words as published in recent articles in the Journal of Korean Society of Dental Hygiene from 2016 to 2018. Methods: Authors' key words published in the Journal of Korean Society of Dental Hygiene were compared with MeSH (Medical Subject Headings) terms. We analyzed appearance frequencies of authors' key words via SPSS (Ver. 21.0). Results: A total of 1,259 key words and 315 articles were included in the analysis. The most frequently used key words were dental hygienist (40 times), oral health (27 times), dental hygienists (23 times), and elderly (14 times). One hundred and eighty-three articles (58.1%) were found, in which at least one key word matched the MeSH terms, and 132 articles (41.9%) were found in which key words did not match the MeSH terms. Two hundred and ninety-three headings (23.3%) of authors' key words published in the Journal of Korean Society of Dental Hygiene completely matched the MeSH terms. Conclusions: Researchers should be educated in the use of authors' key words to accomplish quality improvements.

• Journal of Korean society of Dental Hygiene
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• 제21권5호
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• pp.639-644
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• 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.