1.

Record Nr.

UNINA9910484000703321

Titolo

Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II / / edited by Annalisa Appice, Pedro Pereira Rodrigues, Vítor Santos Costa, João Gama, Alípio Jorge, Carlos Soares

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015

ISBN

3-319-23525-7

Edizione

[1st ed. 2015.]

Descrizione fisica

1 online resource (XLII, 773 p. 198 illus.)

Collana

Lecture Notes in Artificial Intelligence ; ; 9285

Disciplina

006.312

Soggetti

Data mining

Artificial intelligence

Pattern recognition

Information storage and retrieval

Database management

Application software

Data Mining and Knowledge Discovery

Artificial Intelligence

Pattern Recognition

Information Storage and Retrieval

Database Management

Information Systems Applications (incl. Internet)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Sommario/riassunto

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.