Can Latent Features Be Interpreted as Users in Matrix Factorization-Based Recommender Systems?

Reference : Can Latent Features Be Interpreted as Users in Matrix Factorization-Based Recommender...


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/33405

Title :	Can Latent Features Be Interpreted as Users in Matrix Factorization-Based Recommender Systems?
Language :	English
Author, co-author :	Brun, Armelle [> >]
	Aleksandrova, Marharyta [University of Lorraine > > > ; National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”]
	Boyer, Anne [> >]
Publication date :	2014
Main document title :	Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)-Volume 02
Peer reviewed :	Yes
Event name :	2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)
Event date :	from 11-08-2014 to 14-08-2014
Event organizer :	IEEE Computer Society
Permalink :	http://hdl.handle.net/10993/33405
Commentary :	226--233

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