Divergence Based Non-Negative Matrix Factorization for top-N Recommendations

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dc.contributor.authorHaque, Md. Enamul
dc.contributor.authorZobaed, SM
dc.contributor.authorTozal, Mehmet Engin
dc.contributor.authorRaghavan, Vijay
dc.date.accessioned2019-01-02T23:41:36Z
dc.date.available2019-01-02T23:41:36Z
dc.date.issued2019-01-08
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2019.055
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/59485
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectData Science and Digital Collaborations
dc.subjectCollaboration Systems and Technologies
dc.subjectK-L divergence
dc.subjectMatrix factorization
dc.subjectTop N recommendation
dc.titleDivergence Based Non-Negative Matrix Factorization for top-N Recommendations
dc.typeConference Paper
dc.type.dcmiText

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