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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- Appears in
Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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