• Journal of the korean academy of Pediatric Dentistry
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• v.43 no.2
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• pp.123-128
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• 2016

The purpose of this study is to analyze the equality between keywords used in the Journal of the Korean Academy of Pediatric Dentistry and medical subject headings (MeSH). A total of 4,353 English keywords in 1,165 papers from 1998 to 2014 were eligible for this study. We classified them according to equality to MeSH. We assayed patterns of errors in using MeSH, and reviewed frequently used non-MeSH terms. 24.9% of total keywords were completely coincident with MeSH terms, 75.1% were not MeSH terms. The results show that the accordance rate of keywords with MeSH terms in the Journal of the Korean Pediatric Dentistry is at a low level. Therefore, there is a need for authors to understand MeSH more specifically and accurately. Use of proper keywords aligned with the international standards such as MeSH is important to be properly cited. Authors should pay attention and be educated on the correct use of MeSH as keywords.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.15 no.4
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• pp.558-565
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• 2008

Purpose: The purpose of this study was to analyze how accurately authors of the Journal of Korean Academy of Fundamentals of Nursing used MeSH terms as key words. Method: A total of 724 key words used in the 225 papers of Journal of Korean Academy of Fundamentals of Nursing from 2003 to 2007 were compared with MeSH terms. Results: Fifty nine point eight percent of total key words were completely coincident with MeSH terms, 13.5% were entry terms, and 21.8% were not MeSH terms. The coincidence rates for 2003 and 2007 separately were 38.5% and 70.9%. Also, 25.3% of papers precisely used MeSH terms as key words and 8% did not use any MeSH terms. Conclusion: The results show that the coincidence rate of key words with MeSH terms was at a moderate level and gradually increased according to year. However, there is a need for us to understand MeSH more specifically and accurately.

• Journal of the Korean Society of Physical Medicine
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• v.7 no.3
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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 Sasang Constitutional Medicine
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• v.25 no.1
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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.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.141-160
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• 2004

Recent reseach in the field of medical information systems has paid much attention to an ontology based medical terminology system to support clinical study and effective information search. This study aims to conduct research for further application or construction of ontology systems in Korea. This research reviews the theory of concept modeling and ontology. and analyses 4 cases of conceptual modeling of medical tenrminologies by ontology, The findings ot this study display these specific characteristics in medscal ontologies: (UHe standardization of terrrinology on MeSH. (2) The conceptualization of tenninology on UMLS. (l) ane. (2) are showed as untormal ontologies. (3) The theory of ontology integration in ON9, (4) The reference model of medical knowledge with formalization in GALEN. (3) and (4) are showed as formal ontologies. The application and construction of ontology should be differentiated according to the level of the proposed system, and then this analysis will provide useful information for the researcher and developer of the system.

• Journal of Korean society of Dental Hygiene
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• v.19 no.6
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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 KIISE:Software and Applications
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• v.33 no.7
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• pp.636-645
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• 2006

A tenn with more domain specific information has higher level of term specificity. We propose new specificity calculation methods of terms based on information theoretic measures using compositional and contextual information. Specificity of terms is a kind of necessary conditions in tenn hierarchy construction task. The methods use based on compositional and contextual information of terms. The compositional information includes frequency, $tf{\cdot}idf$, bigram and internal structure of the terms. The contextual information of a tenn includes the probabilistic distribution of modifiers of terms. The proposed methods can be applied to other domains without extra procedures. Experiments showed very promising result with the precision of 82.0% when applied to the terms in MeSH thesaurus.

• Journal of the Korean Society for information Management
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• v.21 no.2
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• pp.89-106
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• 2004

There are lots of Web materials in the field of medicine and many search engines classify the medical materials on the Web through directories. But the organization of these directories are wanting in consistency and systematization. In order for manager of search engines to organize medical materials on the Web systematically, this paper suggests several guidelines. NLMC, a special classification system for medicine, need to be applied to develop directories of medicine in search engines. Also, items of the directories should be arranged based on the relevance of subjects among subfields of medical science. For classifying an item to several directories repeatedly, clear criteria should be established. In addition to, controlled vocabularies or glossaries for medicine such as MeSH and the English-Korean, Korean-English Medical Terminology Collection should be used for selection of the name of items in medical directories.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.95-115
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• 2022

The purpose of this study is to transform the sub-categorization terms of the National Science and Technology Standards Classification System into technical keywords by applying a machine learning algorithm. For this purpose, AttentionMeSH was used as a learning algorithm suitable for topic word recommendation. For source data, four-year research status files from 2017 to 2020, refined by the Korea Institute of Science and Technology Planning and Evaluation, were used. For learning, four attributes that well express the research content were used: task name, research goal, research abstract, and expected effect. As a result, it was confirmed that the result of MiF 0.6377 was derived when the threshold was 0.5. In order to utilize machine learning in actual work in the future and to secure technical keywords, it is expected that it will be necessary to establish a term management system and secure data of various attributes.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.901-903
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• 2004

어떤 용어가 전문적인 개념을 많이 내포하고 있을 때 전문성(specificity)이 높다고 말한다. 본 논문에서는 정보이론에 기반한 방법으로 전운용어가 내포하는 전문성을 정량적으로 계산하는 방법을 제안한다. 제안한 방법은 전문용어의 구성정보를 이용하는 방법과 문맥정보를 이용하는 방법으로 나눈다. 구성정보를 이용하는 방법에서는 전문용어틀 구성하는 단어의 빈도수, tf.idf 값, 내부 수식구조 등을 이용하고, 문맥정보를 이용하는 방법에서는 전문용어를 수식하는 단어들의 분포를 이용한다. 제안한 방법은 분야에 독립적으로 적용될 수 있고, 전문용어 생성 절차에 대한 특징을 잘 표현할 수 있는 장정이 있다. MeSH 트리에 포함된 질병명을 대상으로 실험한 결과 82.0%의 정확률을 보였다.