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https://doi.org/10.3938/NPSM.68.647
Build Up of a Subject Classification System from Collective Intelligence
New Phys.: Sae Mulli 2018; 68: 647~654
Published online June 29, 2018;  https://doi.org/10.3938/NPSM.68.647
© 2018 New Physics: Sae Mulli.

Jisung YOON1, Jinhyuk YUN*2, Woo-Sung JUNG†1,3,4

1 Department of Industrial Management Engineering, Pohang University of Science and Technology, Pohang 37673, Korea
2 Future Technology Analysis Center, Korea Institute of Science and Technology Information, Seoul 02456, Korea
3 Department of Physics, Pohang University of Science and Technology, Pohang 37673, Korea and
4 Asia Pacific Center for Theoretical Physics (APCTP), Pohang 37673, Korea
Correspondence to: *jinhyuk.yun@kisti.re.kr, †wsjung@postech.ac.kr
Received March 5, 2018; Revised March 30, 2018; Accepted April 30, 2018.
cc This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Systematized subject classification is essential for funding and assessing scientific projects. Conventionally, classification schemes are founded on the empirical knowledge of the group of experts; thus, the experts' perspectives have influenced the current systems of scientific classification. Those systems archived the current state-of-art in practice, yet the global effect of the accelerating scientific change over time has made the updating of the classifications system on a timely basis vertually impossible. To overcome the aforementioned limitations, we propose an unbiased classification scheme that takes advantage of collective knowledge; Wikipedia, an Internet encyclopedia edited by millions of users, sets a prompt classification in a collective fashion. We construct a Wikipedia network for scientific disciplines and extract the backbone of the network. This structure displays a landscape of science and technology that is based on a collective intelligence and that is more unbiased and adaptable than conventional classifications.
PACS numbers: 07.05.Kf, 89.75.-k, 89.75.Fb
Keywords: Collective intelligence, Science and technology classification, Complex network, Filtering


October 2018, 68 (10)
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