Data stream mining: The bounded rationality

Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/96149

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DC Field	Value	Language
dc.creator	João Gama
dc.date.accessioned	2022-09-08T04:57:00Z	-
dc.date.available	2022-09-08T04:57:00Z	-
dc.date.issued	2013
dc.identifier.issn	0350-5596
dc.identifier.other	sigarra:51349
dc.identifier.uri	https://hdl.handle.net/10216/96149	-
dc.description.abstract	The developments of information and communication technologies dramatically change the data collection and processing methods. Data mining is now moving to the era of bounded rationality. In this work we discuss the implications of the resource constraints impose by the data stream computational model in the design of learning algorithms. We analyze the behavior of stream mining algorithms and present future research directions including ubiquitous stream mining and self-adaption models.
dc.language.iso	eng
dc.rights	restrictedAccess
dc.subject	Engenharia de computadores, Ciências da computação e da informação
dc.subject	Computer engineering, Computer and information sciences
dc.title	Data stream mining: The bounded rationality
dc.type	Artigo em Revista Científica Internacional
dc.contributor.uporto	Faculdade de Economia
dc.identifier.authenticus	P-008-APM
dc.subject.fos	Ciências exactas e naturais::Ciências da computação e da informação
dc.subject.fos	Natural sciences::Computer and information sciences
Appears in Collections:	FEP - Artigo em Revista Científica Internacional

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