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Scientific trend analysis and curation with Korean R&D information

Authors
Kim, Mu Cheol
Issue Date
Sep-2016
Publisher
Springer New York LLC
Keywords
Big data analytics; Scientific issue detection; Social network analysis; Topic detection
Citation
Journal of Supercomputing, v.72, no.9, pp 3663 - 3673
Pages
11
Journal Title
Journal of Supercomputing
Volume
72
Number
9
Start Page
3663
End Page
3673
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/60285
DOI
10.1007/s11227-016-1831-7
ISSN
0920-8542
1573-0484
Abstract
With the development of web, the amount of information from science and technology is generated and managed in web environments. Then, many researchers are interested in the extracting and analyzing scientific issues from various science data. The proposed approach analyzed the issue keywords from metadata in research projects. Furthermore, we extracted the related science data, such as paper and patent, from science document database. The proposed approach performed social network analysis between typical science data. It generated the clusters which represent the scientific topics with time divisions. Moreover, we could deduce the relationship between science data and social data, such as newsletter and blog data.
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Kim, Mu Cheol
소프트웨어대학 (소프트웨어학부)
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