• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.155-162
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• 2006

The medical thesaurus, MeSH (Medical Subject Heading), has been used as a controlled vocabulary thesaurus for English medical paper indexing for a long time. In this paper, we propose an automatic cross language keyword assignment method, which assigns English MeSH index terms to the abstract of a Korean medical paper. We compare the performance with the indexing performance of human indexers and the authors. The procedure of index term assignment is that first extracting Korean MeSH terms from text, changing these terms into the corresponding English MeSH terms, and calculating the importance of the terms to find the highest rank terms as the keywords. For the process, an effective method to solve spacing variants problem is proposed. Experiment showed that the method solved the spacing variant problem and reduced the thesaurus space by about 42%. And the experiment also showed that the performance of automatic keyword assignment is much less than that of human indexers but is as good as that of authors.

• Journal of Korean Library and Information Science Society
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• v.50 no.2
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• pp.191-214
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• 2019

In order to understand the trends of collaborative research in the field of Library and Information Science (LIS) in Korea, this study analyzed bibliometric data and keywords of 5,383 Journal papers by 195 Korean LIS professors from 2000 to 2017 as well as the author credit allocation formulas of 26 Korean university research evaluation criteria. Examination of university research evaluation criteria revealed co-authors' credit level to be generally much lower than that of single authors, which in turn reduces the relative value of collaborative research. As a result, recent journals publish more co-authored papers than single author papers both domestically and internationally. The study also found collaborative research to be less prevalent in private universities than national universities and least prevalent in associate professors among professors. Furthermore, keyword analysis of study data revealed the emerging topics of both domestic and international collaborative research to be those that reflect social phenomena as well as those that relate to information science employing new technologies.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.1
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• pp.145-166
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• 2023

This study aims to analyze the research trends of English-language journals in Korean studies published in Korea. Data were collected from four English journals in Korean studies indexed in A&HCI and SCOPUS. A total of 1,840 were selected, including 768 articles of the Korea Journal, 466 articles of The Review of Korean Studies, 285 articles of the Seoul Journal of Korean Studies, and 321 articles of the Acta Koreana, in connection with content analysis, author analysis, author keyword frequency analysis, and topic modeling. In results, the domain research of Korean studies is Humanities, followed by Social Science, and Arts and Kinesiology. These three sectors have grown significantly in publishing numbers since 2000. The subject period of the study is in the order of the modern period, late Joseon, and Japanese colonial period. Authors from domestic affiliations made up 73.34% of the total, but the proportion of authors belonging to foreign institutions continued to increase. As for author keywords, 'Korea'(41), 'Buddhism'(20), 'Koreanwar'(18), and 'Joseon'(18) were derived as top keywords. In topic modeling, six topics were identified; 'Korean culture, cultural transmission,' 'Korean modern political history,' 'Korean social democratization process,' 'Japanese colonial period,' 'Korean religious philosophy,' and 'Korean ancient history.' Through this study, it was possible to identify the interests in and research areas of the recent international academic community of Korean studies.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.3
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• pp.491-510
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• 2014

As a major factor for efficient management and retrieval of the articles in databases, keywords are classified into uncontrolled keywords and controlled keywords. Most of Korean scholarly databases fail to provide controlled vocabularies to indexing research articles which help users to retrieve relevant papers exhaustively. In this paper, we carried out automatic descriptor assignment experiments to Korean articles using automatic classifiers learned with descriptors in international database. The results of the experiments show that the classifier learning with descriptors in international database can potentially offer controlled vocabularies to Korean scholarly articles having English s. Also, we sought to improve the performance of automatic descriptor assignment using various classifiers and combination of them.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.7-16
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• 2019

The purpose of this study is to identify the characteristics of researches that have been conducted for the last 20 years through analyzing global research trends and evolutions of design articles from 1999 to 2018 with keyword network analysis. For this purpose, we selected 3,569 articles in 22 journals related to design research retrieved from the Scopus database and constructed keyword network model through the author keyword and index keyword. The frequency of the author and index keyword, the centrality of betweenness and degree were analyzed with the keyword network. The results show that design has been applied to various fields for recent 20 years, and the research trends of design could be quantitatively characterized by keyword network analysis. The result of this study could be used to suggest future research topics in the field of design based on quantitative and empirical data.

• Annual Conference on Human and Language Technology
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• 2004.10d
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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 Korea Port Economic Association
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• v.32 no.1
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• pp.79-95
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• 2016

This study identifies themes and trends in maritime economics and logistics by examining 303 papers published in international journals from 2000 to 2014 using keyword network analysis. Network analysis can be used because the collected data follow Zipf's law and the power law. Utilizing the degree centrality and betweenness centrality, we find the important keywords in each five year period and determine the importance of shared keywords. To further explain keyword centralities, we invented a Delta-C algorithm to show the trends of keywords over time. We found that degree centrality is useful for identifying important research themes in each period because it is mainly concerned with the number of connections. On the other hands, betweenness centrality is useful to determine the unique themes that emerge in each of the specific periods.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.41-46
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• 2003

This thesis composes separated words in text for extracting keywords from Japanese, proposes extracting indexing keywords which consist of a compound noun using words and sentences information with the rules in the sentences. It constructs generative rules of compound nouns to be based In dependence as a result of analysing character of keywords in the text not the same way as before. To hold other extracting keywords and the content of sentence, and suggest how to decide importance concerned some restriction and repetition of words about generative rules. To verify the validity of keywords extracting, we have used titles and abstracts from Japanese thesis 65 files about natural language and/or voice processing, and obtain 63% in outputting one in the top rank.

• Journal of the Korean Society for information Management
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• v.35 no.2
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• pp.89-114
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• 2018

Research on changes in research trends in academic disciplines is a method that enables observation of not only the detailed research subject and structure of the field but also the state of change in the flow of time. Therefore, in this study, in order to observe the changes of research trend in library and information science field in Korea, co-word analysis was conducted with Korean author keywords from three types of journals which were listed in the Korea Citation Index(KCI) and have top citation impact factor were selected. For the time series analysis, the 15-year research period was accumulated in 5-years units, and divided into 2003~2007, 2003~2012, and 2003~2017. The keywords which limited to the frequency of appearance 10 or more, respectively, were analyzed and visualized. As a result of the analysis, during the period from 2003 to 2007, the intellectual structure composed with 25 keywords and 8 areas was confirmed, and during the period from 2003 to 2012, the structure composed by 3 areas 17 sub-areas with 76 keywords was confirmed. Also, the intellectual structure during the period from 2003 to 2017 was crowded into 6 areas 32 consisting of a total of 132 keywords. As a result of comprehensive period analysis, in the field of library and information science in Korea, over the past 15 years, new keywords have been added for each period, and detailed topics have also been subdivided and gradually segmented and expanded.

• 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.