Deep reinforcement learning in recommender systems: A survey and new perspectives

Chen, X; Yao, L; McAuley, J; Zhou, G; Wang, X

Deep reinforcement learning in recommender systems: A survey and new perspectives

Chen, X Yao, L McAuley, J Zhou, G Wang, X

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Knowledge-Based Systems, 2023, 264, pp. 110335
Issue Date:: 2023-01

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Field	Value	Language
dc.contributor.author	Chen, X
dc.contributor.author	Yao, L
dc.contributor.author	McAuley, J
dc.contributor.author	Zhou, G
dc.contributor.author	Wang, X https://orcid.org/0000-0001-9582-3445
dc.date.accessioned	2023-02-02T09:49:49Z
dc.date.available	2023-02-02T09:49:49Z
dc.date.issued	2023-01
dc.identifier.citation	Knowledge-Based Systems, 2023, 264, pp. 110335
dc.identifier.issn	0950-7051
dc.identifier.uri	http://hdl.handle.net/10453/165854
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Knowledge-Based Systems
dc.relation.isbasedon	10.1016/j.knosys.2023.110335
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services, 17 Psychology and Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Deep reinforcement learning in recommender systems: A survey and new perspectives
dc.type	Journal Article
utslib.citation.volume	264
utslib.for	08 Information and Computing Sciences
utslib.for	15 Commerce, Management, Tourism and Services
utslib.for	17 Psychology and Cognitive Sciences
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/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	open_access	*
dc.date.updated	2023-02-02T09:49:47Z
pubs.publication-status	Accepted
pubs.volume	264

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