• Journal of Korean Library and Information Science Society
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• v.54 no.1
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• pp.45-68
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• 2023

This study aims to investigate the awareness and experiences of domestic researchers regarding data publishing, which has been recognized as a new channel of data sharing as scholarly communication evolves in the open science environment. A survey is conducted among researchers from five government-funded research institutes in the field of science and technology and members of the GeoAI Data Society to confirm the awareness of data publishing. As a result of the study, domestic researchers recognized providing explanations for data, stable access to data, citation, and quality assurance through peer review as the advantages of data journals. On the contrary, a low level of recognition for data paper as one of the research outputs was presented. With regard to the properties of data publication, the respondents answered that the data description, metadata description, and permanent identifiers are highly related, however, their recognition of the relation between the properties of data publication and the data submission to a repository and data peer review was relatively low. Finally, to expand the data publication, the need for the development of an editorial system that supports data paper peer review and cross-linking to a data repository as well as the development of a repository that supports data citation was identified. This study on the domestic researchers' experience and awareness of data publishing can provide insights for the implementation of data publishing services and infrastructure in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.955-960
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• 2012

In this paper, we analysis a competition to organize knowledge map as initial prepare stage based on intellectual property. We also propose the method that can be used to constitute knowledge map related in area to use basic data. In order to extract analysis data, we choose LED as an analysis technology. We provide the result of total analysis for LED application area through analysis of patent level after we extract recent patent ratio, activity index, patent family size, cites per patent as center of patent data.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.325-350
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• 2023

This study focuses on the impact of research data metadata quality evaluation index on the revitalization of K-BDS, a research data platform in the bio field, and examines the mediating effect of motivation factors for utilizing the platform. The investigation employs a structural equation model analysis and bootstrap analysis to explore the interrelationships among the three variables. The findings demonstrate that researchers who prioritize the quality of metadata display higher motivation to use the research data platform, leading to an intention to activate the platform. The study also confirms the mediating effect of motivation factors. Moreover, a comprehensive understanding of the sub-factors within each variable is attained through regression analysis and Sobel test. The results highlight that enhancing searchability is crucial to activate research data sharing in the bio field, while improving discoverability is vital for research data reuse. Interestingly, the study reveals that citationability does not significantly impact platform activation. As a conclusion, to foster platform activation, it is imperative to provide systematic support by enhancing metadata quality. This improvement can not only increase trust in the platform but also institutionally solidify the benefits of citation.

• Journal of the Korean Society for information Management
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• v.32 no.1
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• pp.153-169
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• 2015

The combined approach of using ego-centric network analysis and dynamic citation network analysis for refining the result of LDA-based topic modeling was suggested and examined in this study. Tow datasets were constructed by collecting Web of Science bibliographic records of White LED and topic modeling was performed by setting a different number of topics on each dataset. The multi-assigned top keywords of each topic were re-assigned to one specific topic by applying an ego-centric network analysis algorithm. It was found that the topical cohesion of the result of topic modeling with the number of topic corresponding to the lowest value of perplexity to the dataset extracted by SPLC network analysis was the strongest with the best values of internal clustering evaluation indices. Furthermore, it demonstrates the possibility of developing the suggested approach as a method of multi-faceted research trend detection.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.3
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• pp.5-17
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• 2012

In citation analysis, author names are often used as the unit of analysis and some authors are indexed under the same name in bibliographic databases where the citation counts are obtained from. There are many techniques for author name disambiguation, using supervised, unsupervised, or semisupervised learning algorithms. Unsupervised approach uses machine learning algorithms to extract necessary bibliographic information from large-scale databases and digital libraries, while supervised approaches use manually built training datasets for clustering author groups for combining them with learning algorithms for author name disambiguation. The study examines various techniques for author name disambiguation in the hope for finding an aid to improve the precision of citation counts in citation analysis, as well as for better results in information retrieval.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.50.3-50.3
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• 2015

고립된 은하쌍 내의 두 은하의 스핀 각운동량의 각도 차이의 분포를 구하고 이를 통계적으로 분석한 결과를 관측 데이터와 수치 시뮬레이션 데이터 간에 비교함으로써 ${\Lambda}CDM$ 모형이 아닌 다른 우주 모형의 주요 변수를 규제할 수 있다. 이 연구에서는 결합된 암흑 에너지 (coupled dark energy, cDE) 모형의 주요 변수인 결합 함수를 규제하기 위해 서로 다른 조건의 cDE 모형과 ${\Lambda}CDM$ 모형에 따라서 생성한 수치 데이터의 스핀 정렬을 Argudo-Fernandez et al. (2015) 에서 인용한 관측 데이터의 스핀 정렬과 비교하였고, ${\Lambda}CDM$ 모형과 대부분의 cDE 모형의 수치 데이터는 관측 데이터와 부합하나 일부 cDE 모형은 부합하지 않아서 제외될 가능성이 높음을 확인하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.718-720
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• 2005

딥-서버마이크론 기술에서, 버스 상에서의 전력 소모를 최소화하는 것은 가장 중요한 설계 목표들 가운데 하나이다. 전력 소모를 줄이기 위해 일반적으로 사용되고 있는 효과적인 기법들은 근본적으로 데이터 압축 또는 데이터 인코딩을 이용하고 있지만 압축과 인코딩을 모두 사용한 기법은 현재까지 알려져 있지 않다. 본 논문은 버스에서의 데이터 전송 시 발생하는 전력소모량을 크로스톡 지연을 완전히 제거함과 동시에 최대한 줄이는 통합된 데이터 압축 및 인코딩 알고리즘을 제안한다. 전력 소모를 줄이는 문제를 셀프 천이와 크로스-커플된 천이 양에 대한 가중 합을 최소화하는 문제로 형상화하여 풀었으며, 이 과정에서 자주-인용 데이터에 기반한 압축과 셀프-쉴드 인코딩이라는 개념을 활용하였다. 벤치마크를 사용한 실험에서 우리는 제안한 방법을 사용하면, 기존의 순차적인 압축 및 인코딩 적용 방식보다 $7.9\%-39.4\%$ 더 적은 전력 소모를 가짐을 알 수 있었다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.241-242
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• 2021

본 논문에서는 2020년 1월부터 2020년 8월까지 8개월간의 유통되었던 코로나 19와 관련된 뉴스 데이터를 이용하여 기간 및 지역별 단어의 빈도수를 구하고, 그 결과를 활용해 코로나 19와의 상관관계를 분석하고, 시각화하였다. 뉴스데이터는 한국언론진흥재단에서 운영하는 뉴스 빅데이터 시스템인 '빅카인즈'에서 수집된 데이터를 이용하였다. 본 논문에서 웹서비스를 활용해 시각화하였으며 지역과 기간을 선택하면 분석한 결과를 불러와 전체 지역대비 선택한 지역의 뉴스 빈도수, 선택한 지역의 주요 키워드, 주요 키워드의 지역별 일자별 변화 등을 보여주고 있다. 이러한 시각화를 통해 이전에 발생되었던 사건에 대해 주요 키워드와 코로나 19의 상관관계를 쉽게 파악을 할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.524-526
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• 2024

컴퓨터 과학(CS) 분야는 다른 학문 분야에 비해 연구 동향이 빠르게 변하는 특성을 가지고 있다. 그래프 마이닝에서 활발히 사용되는 CS 분야 논문 데이터셋를(e.g., Cora, Citeseer, DBLP)은 오래된 논문을 중심으로 구성되어 있어 이러한 특성을 제대로 반영하지 못하는 한계가 있다. 따라서 본논문에서는 CS 분야의 최신 트렌드를 반영하는 논문 데이터셋을 제안한다. 이를 위해, 우리는 CS 분야 논문을 활발히 공개하는 플랫폼인 arXiv 에서 2007 년부터 2023 년까지 해당 플랫폼에서 공개된 논문들을 수집하고, 이를 기반으로 공저자 그래프 및 인용 그래프로 구축한다. 해당 데이터셋을 대상으로 폭넓은 분석을 통해, 우리가 구축한 데이터셋이 실세계 그래프 네트워크 특성을 잘 반영하고 있음을 보인다. 또한, 향휴에 해당 데이터셋을 사용하려는 연구자들을 위해, 해당 데이터셋에서의 기존 그래프 기반 응용들의 노드 분류 성능을 제시한다.

• Journal of Korea Technology Innovation Society
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• v.19 no.4
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• pp.768-798
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• 2016

This study started from the awareness of the issue if the citation index newly introduced to evaluate the quality of papers satisfies the proper timing matter, which is a component of performance indicators for the evaluation of government-funded R&D institutes. Accordingly, the study will propose improvement ways to shift the previous evaluation system to quality evaluation for mission-oriented R&D institutes by analysing and using the periodical characteristics such as citation half-life and immediacy index of papers. As a result, it turned out that the speed of academic change is getting faster in proportion to the dependency on the technological development but that the citation speed in the field of public technology is relatively slower and the speed of knowledge transfer in the fields related to industry is faster. In addition, the citation index among the R&D fields showed no differences, and the minimum period for citation index measurement with validity should be over 6 years. The problems of evaluation for mission-oriented R&D institutes were deducted based on the technical and statistical analysis results of the temporal characteristic of citation necessary for quality evaluation of performance among R&D fields. To solve the problems, policy alternatives for object and valid quality evaluation were proposed from the points of evaluation period and evaluation criteria.