Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II /

The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed a...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Appice, Annalisa (Editor ), Rodrigues, Pedro Pereira (Editor ), Santos Costa, Vítor (Editor ), Gama, João (Editor ), Jorge, Alípio (Editor ), Soares, Carlos (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Colección:Lecture Notes in Artificial Intelligence, 9285
Temas:
Data mining.
Artificial intelligence.
Pattern recognition systems.
Information storage and retrieval systems.
Database management.
Application software.
Data Mining and Knowledge Discovery.
Artificial Intelligence.
Automated Pattern Recognition.
Information Storage and Retrieval.
Database Management.
Computer and Information Systems Applications.
Acceso en línea:Texto Completo
Descripción
Sumario:The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.
Descripción Física:XLII, 773 p. 198 illus. online resource.
ISBN:9783319235257
ISSN:2945-9141 ;

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