μ-cf2vec:  Representation Learning for Personalized Algorithm Selection in Recommender Systems

Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/132901

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DC Field	Value	Language
dc.creator	Tomás Trigueiros de Sousa Pereira
dc.date.accessioned	2025-11-09T14:38:50Z	-
dc.date.available	2025-11-09T14:38:50Z	-
dc.date.issued	2020-07-28
dc.date.submitted	2021-03-12
dc.identifier.other	sigarra:445362
dc.identifier.uri	https://hdl.handle.net/10216/132901	-
dc.description	Neste momento Collaborative filtering é a tecnica que permite alcancar resultados do estado daarte em problemas de sistemas de recomendação. Existem várias implementações desta técnica cada uma com as suas características.
dc.description.abstract	Collaborative filtering has becoming standard approach to achieve state of the art results in rec-ommendation systems problems. There are multiples implementations of this technique, each onethem with its own characteristics.
dc.language.iso	eng
dc.rights	openAccess
dc.subject	Ciências da engenharia e tecnologias
dc.subject	Engineering and technology
dc.title	μ-cf2vec: Representation Learning for Personalized Algorithm Selection in Recommender Systems
dc.type	Dissertação
dc.contributor.uporto	Faculdade de Engenharia
dc.identifier.doi	10.34626/w82g-ym33
dc.subject.fos	Ciências da engenharia e tecnologias
dc.subject.fos	Engineering and technology
thesis.degree.discipline	Mestrado Integrado em Engenharia Electrotécnica e de Computadores
thesis.degree.grantor	Faculdade de Engenharia
thesis.degree.grantor	Universidade do Porto
thesis.degree.level	1
Appears in Collections:	FEUP - Dissertação

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