A bibliometric analysis of aggregation operators

Blanco-Mesa, F; León-Castro, E; Merigó, JM

A bibliometric analysis of aggregation operators

Blanco-Mesa, F León-Castro, E Merigó, JM

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Applied Soft Computing Journal, 2019, 81, pp. 1-21
Issue Date:: 2019-08-01

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Field	Value	Language
dc.contributor.author	Blanco-Mesa, F
dc.contributor.author	León-Castro, E
dc.contributor.author	Merigó, JM
dc.date.accessioned	2021-02-23T12:05:31Z
dc.date.available	2021-02-23T12:05:31Z
dc.date.issued	2019-08-01
dc.identifier.citation	Applied Soft Computing Journal, 2019, 81, pp. 1-21
dc.identifier.issn	1568-4946
dc.identifier.issn	1872-9681
dc.identifier.uri	http://hdl.handle.net/10453/146343
dc.description.abstract	© 2019 Elsevier B.V. Aggregation operators consist of mathematical functions that enable the combining and processing of different types of information. The aim of this work is to present the main contributions in this field by a bibliometric review approach. The paper employs an extensive range of bibliometric indicators using the Web of Science (WoS) Core Collection and Scopus datasets. The work considers leading journals, articles, authors, institutions countries and patterns. This paper highlights that Xu is the most productive author and Yager is the most influential author in the field. Likewise, China is leading the field with many new researchers who have entered the field in recent years. This discipline has been strengthening to create a unique theory and will continue to expand with many new theoretical developments and applications.
dc.language	English
dc.publisher	Elsevier
dc.relation.ispartof	Applied Soft Computing Journal
dc.relation.isbasedon	10.1016/j.asoc.2019.105488
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0102 Applied Mathematics, 0801 Artificial Intelligence and Image Processing, 0806 Information Systems
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	A bibliometric analysis of aggregation operators
dc.type	Journal Article
utslib.citation.volume	81
utslib.for	0102 Applied Mathematics
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0806 Information Systems
utslib.for	0102 Applied Mathematics
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0806 Information Systems
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2021-02-23T12:05:24Z
pubs.publication-status	Published
pubs.volume	81

Abstract:

© 2019 Elsevier B.V. Aggregation operators consist of mathematical functions that enable the combining and processing of different types of information. The aim of this work is to present the main contributions in this field by a bibliometric review approach. The paper employs an extensive range of bibliometric indicators using the Web of Science (WoS) Core Collection and Scopus datasets. The work considers leading journals, articles, authors, institutions countries and patterns. This paper highlights that Xu is the most productive author and Yager is the most influential author in the field. Likewise, China is leading the field with many new researchers who have entered the field in recent years. This discipline has been strengthening to create a unique theory and will continue to expand with many new theoretical developments and applications.

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http://hdl.handle.net/10453/146343