Network community-based Technological cooperation identification

Huang, L; Miao, W; Zhang, Y; Yu, H; Wang, K

Network community-based Technological cooperation identification

Huang, L Miao, W Zhang, Y

Yu, H Wang, K

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Publisher:: INT SOC SCIENTOMETRICS & INFORMETRICS-ISSI
Publication Type:: Conference Proceeding
Citation:: ISSI 2017 - 16th International Conference on Scientometrics and Informetrics, Conference Proceedings, 2017, pp. 1754-1765
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Huang, L
dc.contributor.author	Miao, W
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-7731-0301
dc.contributor.author	Yu, H
dc.contributor.author	Wang, K
dc.contributor.editor	Atanassova, I
dc.contributor.editor	Bertin, M
dc.contributor.editor	Mayr, P
dc.date	2017-10-16
dc.date.accessioned	2024-02-29T05:48:35Z
dc.date.available	2024-02-29T05:48:35Z
dc.date.issued	2017-01-01
dc.identifier.citation	ISSI 2017 - 16th International Conference on Scientometrics and Informetrics, Conference Proceedings, 2017, pp. 1754-1765
dc.identifier.issn	2175-1935
dc.identifier.uri	http://hdl.handle.net/10453/175973
dc.description.abstract	Technological cooperation becomes necessary in extending technological application and improving market competitiveness, and thus, it is important to identify collaborative technologies that meet strategic purposes. This paper aims to construct a technological network based on the core terms derived from patent documents to help technology owners achieve such target. A four-step analytic framework is constructed, including: 1) community division, which allows the selection of cooperative technology to be controlled within a more relevant technical range; 2) indicator analysis that can be used to understand the technological situation within the community from three main aspects, i.e., degree, clustering coefficient and line weight; 3) the purpose of cooperation, which is an important basis for the selection of cooperative technology; and 4) technology selection, which is to combine cooperation purposes and indicator analysis to select technology. Finally, a case study on China's artificial intelligence (AI) technology is conducted to demonstrate the feasibility of this method, and the findings will help decision making in related AI fields.
dc.language	en
dc.publisher	INT SOC SCIENTOMETRICS & INFORMETRICS-ISSI
dc.relation.ispartof	ISSI 2017 - 16th International Conference on Scientometrics and Informetrics, Conference Proceedings
dc.relation.ispartof	16th International Conference on Scientometrics and Informetrics (ISSI)
dc.relation.ispartofseries	Proceedings of the International Conference on Scientometrics and Informetrics
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Network community-based Technological cooperation identification
dc.type	Conference Proceeding
utslib.location.activity	Wuhan Univ, Wuhan, PEOPLES R CHINA
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
utslib.copyright.status	open_access	*
dc.date.updated	2024-02-29T05:48:34Z
pubs.finish-date	2017-10-20
pubs.publication-status	Published
pubs.start-date	2017-10-16

Abstract:

Technological cooperation becomes necessary in extending technological application and improving market competitiveness, and thus, it is important to identify collaborative technologies that meet strategic purposes. This paper aims to construct a technological network based on the core terms derived from patent documents to help technology owners achieve such target. A four-step analytic framework is constructed, including: 1) community division, which allows the selection of cooperative technology to be controlled within a more relevant technical range; 2) indicator analysis that can be used to understand the technological situation within the community from three main aspects, i.e., degree, clustering coefficient and line weight; 3) the purpose of cooperation, which is an important basis for the selection of cooperative technology; and 4) technology selection, which is to combine cooperation purposes and indicator analysis to select technology. Finally, a case study on China's artificial intelligence (AI) technology is conducted to demonstrate the feasibility of this method, and the findings will help decision making in related AI fields.

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http://hdl.handle.net/10453/175973