• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.121-142
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• 2014

This study aims to investigate the importance of author keyword with analysis the position of author keyword in journal. In the first stage, an analysis was carried out on the position of author keyword. We examined the importance of author keyword by using degree centrality, closeness centrality, betweenness centrality, eigenvector centrality and effective size of structural hole. In the next stage, We performed analysis on correlation between network centrality measures and the position of author keyword. The result of correlation analysis on network centrality measures and the position of author keyword shows that there are the more significant areas of the result of the correlation analysis on degree centrality, betweenness centrality and the position of keyword. In addition, These results show that we need to consider that the possible way as measuring the importance of author keyword in journal is not only a term frequency but also degree centrality and betweenness centrality.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.3
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• pp.209-218
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• 2009

This study analyzed the authorship tendency of the authors in the specific organizations. The SCI articles of the authors in H medical center, from 2000 to 2008, were extracted and indexed by the authors. The authorship tendency was analyzed on transience and continuance. As results of analysis, authorship tendency showed continuing tendency not transient tendency. Specifically, the publication rate by new authors was high as the average 39.17% but the publication rate by pre-existence authors, which consisted of the publication rate(16.83%) of reclosing authors and publication rate (44%) of the series author, was relatively higher as the average 60.83%. Also, the extinction author rate of new authors was relatively low as the average 28.2%. the non-flexible publication probability by the author in the specific year was very high as the average 76%. As a result, this study would be used as basic data for the research result management of the organization.

• The KIPS Transactions:PartB
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• v.16B no.3
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• pp.225-232
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• 2009

Author name disambiguation is essential for improving performance of document indexing, retrieval, and web search. Author name disambiguation resolves the conflict when multiple authors share the same name label. This paper introduces a novel approach which exploits ontologies and WordNet-based category utility for author name disambiguation. Our method utilizes author knowledge in the form of populated ontology that uses various types of properties: titles, abstracts and co-authors of papers and authors' affiliation. Author ontology has been constructed in the artificial intelligence and semantic web areas semi-automatically using OWL API and heuristics. Author name disambiguation determines the correct author from various candidate authors in the populated author ontology. Candidate authors are evaluated using proposed WordNet-based category utility to resolve disambiguation. Category utility is a tradeoff between intra-class similarity and inter-class dissimilarity of author instances, where author instances are described in terms of attribute-value pairs. WordNet-based category utility has been proposed to exploit concept information in WordNet for semantic analysis for disambiguation. Experiments using the WordNet-based category utility increase the number of disambiguation by about 10% compared with that of category utility, and increase the overall amount of accuracy by around 98%.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.9-14
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• 2018

This study aims to investigate an importance of Author keyword with analysis the position of author keyword. An analysis was carried out on the position of author keyword. we examined an importance of Author keyword by using degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. In the next stage, we performed analysis on correlation between network centrality measures and the position of keyword. As a result, degree centrality, closeness centrality, betweenness centrality, eigenvector centrality both has a high value in 4th author keyword order. eigenvector centrality was the comparatively effective method to separate of author keyword order method than other 3 centrality. Correlation analysis result shows that the network analysis value are increasing in order. This study has significance in that it was able to examine the author keyword behavior. Future research is needed to identify and supplement future situational factors, behavior, and psychology.

• Proceedings of the Korean Society for Information Management Conference
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• 2001.08a
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• pp.81-84
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• 2001

본 연구는 학술커뮤니케이션에서 활용되는 온라인 전자출판물의 이용과 인용도에 대한 상관관계 분석과 유용성의 차이를 평가하고자 하는 연구목적을 수행하기 위해 학술지에 게재된 게재기사에 온라인 전자출판물을 인용한 저자들을 대상으로 이용도와 인용도를 조사하였으며, 학술지에 게재된 게재기사에 인용된 온라인 전자 출판물의 사회과학분야와 자연과학분야 간 유용성에 대해 비교 분석하였다. 학술지에 게재된 게재기사에 온라인 전자출판물을 인용한 저자의 이용도와 학술지에 인용된 온라인 전자출판물의 수와 인용비율간의 상관관계는 저자들의 온라인 전자출판물 주당 이용시간과 이용종수가 증가하더라도 저자들이 학술지에 인용하는 온라인 전자출판물의 수와 인용비율은 증가하지 않는 것으로 나타났다. 사회과학분야와 자연과학분야 간에 있어서 학술지에 인용되는 온라인 전자출판물의 유용성에는 차이가 없었다. 따라서 학술지의 게재기사에 온라인 전자출판물을 인용한 저자들이 온라인 전자출판물을 많이 이용하는 것과 온라인 전자출판물을 실제로 인용하는 것에는 상관관계가 없으며, 측정요소를 통하여 평가한 사회과학 분야와 자연과학분야에서 온라인 전자출판물의 유용성에는 통계적으로 유의미한 차이가 없는 것으로 나타났다.

• Journal of Information Management
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• v.42 no.1
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• pp.47-62
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• 2011

While an ideal author graph should have its nodes to represent authors, automatically-generated author graphs mostly use author names as their nodes due to the difficulty of resolving author names into individuals. However, employing author names as nodes of author graphs merges namesakes, otherwise separate nodes in the author graph, into the same node, which may distort the characteristics of the author graph. This study proposes an algorithm which resolves author ambiguities based on co-authorship and then yields an author graph consisting of not author name nodes but author nodes. Scientific collaboration relationship this algorithm depends on tends to produce the clustering results which minimize the over-clustering error at the expense of the under-clustering error. In experiments, the algorithm is applied to the real citation records where Korean namesakes occur, and the results are discussed.

• Journal of the Korean Society for information Management
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• v.25 no.3
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• pp.27-39
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• 2008

In bibliographic data, the use of personal names to indicate authors makes it difficult to specify a particular author since there are numerous authors whose personal names are the same. Resolving same-name author instances into different individuals is called author resolution, which consists of two steps: calculating author similarities and then clustering same-name author instances into different person groups. Author similarities are computed from similarities of author-related bibliographic features such as coauthors, titles of papers, publication information, using supervised or unsupervised methods. Supervised approaches employ machine learning techniques to automatically learn the author similarity function from author-resolved training samples. So far however, a few machine learning methods have been investigated for author resolution. This paper provides a comparative evaluation of a variety of recent high-performing machine learning techniques on author disambiguation, and compares several methods of processing author disambiguation features such as coauthors and titles of papers.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.81-100
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• 2024

This study analyzed the national diversity of journal editors and authors, focusing on international journals in library and information science, and quantified it through Simpson's Diversity Index. In addition, LIS journals were clustered according to diversity indicators and their characteristics were analyzed, and it was also confirmed whether nationality diversity of editorial members could induce nationality diversity of authors. As a result of the analysis, first, the diversity index of the editors of the LIS (Library & Information Science) international journal was found to be 0.64, which is less than the diversity of the authors, which is 0.76. It was confirmed that as the diversity of nationalities among editorial committee members increases, it is possible to attract authors of various nationalities (r = .79). Second, journals in the IS (Information Science) field showed a high index before or after 0.8 for both editorial members and author contributing countries, but those in the LS (Library Science) field showed relatively low scores, especially among the editorial members, with a very low index of 0.48. Third, the United States has the highest share of both authors and editors, and in particular, it has been confirmed that the LS field has an overwhelming share of 53.39% of editors. On the other hand, in Asian countries, including Korea, the ratio of contributions as editors compared to contributions as authors was found to be lower than in the United States and European countries.

• Proceedings of the Korean Society for Information Management Conference
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• 2014.08a
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• pp.119-122
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• 2014

본 연구는 교육학 분야에서 국내 학술 논문 저자키워드 출현 순서에 의미가 있는지 알아보기 위하여 저자키워드 출현 순서별로 빈도를 조사하고 동 저자 키워드가 제목에 출현하는지를 살펴본 후, 학술논문 저자키워드 출현 순서에 따른 빈도가 저자키워드의 논문 제목 출현 빈도에 미치는 영향에 대해 연구하고자 한다. 연구의 배경은 구조적 학술용어사전의 구축과 관련해서 효율적인 용어 선정이나 용어 분류 방법을 찾는 것이다. 연구의 목적을 위해 교육학 분야 저자키워드의 출현 빈도수가 1인 것을 제외하고 고빈도 순으로 400개 용어를 추출하였다. 저자키워드의 몇 번째 출현 순서가 저자키워드의 제목 출현에 가장 큰 영향을 미치는지 알아본 결과, 저자키워드의 첫 번째 출현이 아닌 두 번째 출현이 가장 큰 영향을 미친다는 것을 알 수 있었다.

• Journal of the Korean Society for information Management
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• v.28 no.1
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• pp.123-144
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• 2011

This study compared Author Profiling Analysis(APA) to Author Co-Citation Analysis (ACA). The former is a new analytic technique on the intellectual structure of a science whereas the latter is a traditional analytic technique. The purpose of this study was to propose appropriate methods to analyze intellectual structure of a science in the Korean research environment. In order to achieve the goal, this study adopted APA using Text Mining for analysis on the intellectual structure of a science rather than relying on citation index in order to determine a potential utility of the new analytic technique that can identify the intellectual structure.