Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/100872
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dc.contributor.authorJi, K.-
dc.contributor.authorShen, H.-
dc.date.issued2015-
dc.identifier.citationKnowledge-Based Systems, 2015; 83(1):42-50-
dc.identifier.issn0950-7051-
dc.identifier.issn1872-7409-
dc.identifier.urihttp://hdl.handle.net/2440/100872-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityKe Ji, Hong Shen-
dc.language.isoen-
dc.publisherElsevier-
dc.rights© 2015 Elsevier B.V. All rights reserved.-
dc.source.urihttp://dx.doi.org/10.1016/j.knosys.2015.03.008-
dc.subjectRecommender systems; matrix factorization; tag-keyword; cold start; scalability-
dc.titleAddressing cold-start: scalable recommendation with tags and keywords-
dc.typeJournal article-
dc.identifier.doi10.1016/j.knosys.2015.03.008-
dc.relation.granthttp://purl.org/au-research/grants/arc/DP150104871-
pubs.publication-statusPublished-
dc.identifier.orcidShen, H. [0000-0002-3663-6591] [0000-0003-0649-0648]-
Appears in Collections:Aurora harvest 7
Computer Science publications

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