RecRisk: An enhanced recommendation model with multi-facet risk control

Xiao, Y Pei, Q Yao, L Wang, X

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Field	Value	Language
dc.contributor.author	Xiao, Y
dc.contributor.author	Pei, Q
dc.contributor.author	Yao, L
dc.contributor.author	Wang, X https://orcid.org/0000-0001-9582-3445
dc.date.accessioned	2020-06-20T23:18:23Z
dc.date.available	2020-06-20T23:18:23Z
dc.date.issued	2020-11
dc.identifier.citation	Expert Systems with Applications, 2020, 158, pp. 113561-113561
dc.identifier.issn	0957-4174
dc.identifier.uri	http://hdl.handle.net/10453/141589
dc.language	en
dc.publisher	Elsevier BV
dc.relation	http://purl.org/au-research/grants/arc/DE180100251
dc.relation.ispartof	Expert Systems with Applications
dc.relation.isbasedon	10.1016/j.eswa.2020.113561
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	01 Mathematical Sciences, 08 Information and Computing Sciences, 09 Engineering
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	RecRisk: An enhanced recommendation model with multi-facet risk control
dc.type	Journal Article
utslib.citation.volume	158
utslib.for	01 Mathematical Sciences
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
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 Computer Science
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	open_access	*
dc.date.updated	2020-06-20T23:18:18Z
pubs.publication-status	Accepted
pubs.volume	158

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