Machine Learning and Knowledge Discovery in Databases
Editat de Toon Calders, Floriana Esposito, Eyke Hüllermeier, Rosa Meoen Limba Engleză Paperback – 23 sep 2014
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (3) | 336.07 lei 6-8 săpt. | |
| Springer – 23 sep 2014 | 336.07 lei 6-8 săpt. | |
| Springer Berlin, Heidelberg – 12 sep 2014 | 341.47 lei 6-8 săpt. | |
| Springer – 22 sep 2014 | 345.29 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783662448441
ISBN-10: 3662448440
Pagini: 572
Ilustrații: XXXVI, 533 p. 155 illus.
Dimensiuni: 155 x 235 x 31 mm
Greutate: 0.86 kg
Ediția:2014
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3662448440
Pagini: 572
Ilustrații: XXXVI, 533 p. 155 illus.
Dimensiuni: 155 x 235 x 31 mm
Greutate: 0.86 kg
Ediția:2014
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
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Public țintă
ResearchCuprins
Dynamic networks and knowledge discovery.- Interactions between data mining and natural language processing.- Mining ubiquitous and social environments.- Statistically sound data mining.- Machine learning for urban sensor data.- Multi-target prediction.- Representation learning.- Neural connectomics: from imaging to connectivity.- Data analytics for renewable energy integration.- Linked data for knowledge discovery.- New frontiers in mining complex patterns.- Experimental economics and machine learning.- Learning with multiple views: applications to computer vision and multimedia mining.- Generalization and reuse of machine learning models over multiple contexts.- Predictive web analytics.
Textul de pe ultima copertă
This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.