An optimally weighted user- and item-based collaborative filtering approach to predicting baseline data for Friedreich's Ataxia patients

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/22117

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DC Field	Value	Language
dc.contributor.author	Yue, W	-
dc.contributor.author	Wang, Z	-
dc.contributor.author	Liu, W	-
dc.contributor.author	Tian, B	-
dc.contributor.author	Lauria, S	-
dc.contributor.author	Liu, X	-
dc.date.accessioned	2021-01-18T16:22:00Z	-
dc.date.available	2020-08-29	-
dc.date.available	2021-01-18T16:22:00Z	-
dc.date.issued	2020	-
dc.identifier.citation	Neurocomputing, 2020, 419 (2 January 2021), pp. 287 - 294	en_US
dc.identifier.issn	0925-2312	-
dc.identifier.uri	http://bura.brunel.ac.uk/handle/2438/22117	-
dc.description.sponsorship	Seventh Framework Programme of the European Union; Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany.	en_US
dc.format.extent	287 - 294	-
dc.language	English	-
dc.language.iso	en	en_US
dc.publisher	Elsevier	en_US
dc.subject	Friedreich’s Ataxia	en_US
dc.subject	Collaborative filtering	en_US
dc.subject	Positive correlation	en_US
dc.subject	Negative correlation	en_US
dc.subject	Particle swarm optimization	en_US
dc.title	An optimally weighted user- and item-based collaborative filtering approach to predicting baseline data for Friedreich's Ataxia patients	en_US
dc.type	Article	en_US
dc.identifier.doi	http://dx.doi.org/10.1016/j.neucom.2020.08.031	-
dc.relation.isPartOf	Neurocomputing	-
pubs.issue	2 January 2021	-
pubs.publication-status	Published	-
pubs.volume	419	-
dc.identifier.eissn	1872-8286	-
Appears in Collections:	Dept of Computer Science Embargoed Research Papers

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