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Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part I

Toon Calders, Floriana Esposito, Eyke Hüllermeier, Rosa Meo (Herausgeber)

Buch | Softcover

XLIV, 709 Seiten

2014 | 2014
Springer Berlin (Verlag)
978-3-662-44847-2 (ISBN)

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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.

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.

Erscheint lt. Verlag	12.9.2014
Reihe/Serie	Lecture Notes in Artificial Intelligence
Reihe/Serie	Lecture Notes in Computer Science
Zusatzinfo	XLIV, 709 p. 183 illus.
Verlagsort	Berlin
Sprache	englisch
Maße	155 x 235 mm
Gewicht	1139 g
Themenwelt	Informatik ► Datenbanken ► Data Warehouse / Data Mining
Schlagworte	Artificial Intelligence • Association Rules • Clustering • Collaborative Filtering • content ranking • data analytics • Data Mining • data stream mining • Knowledge Discovery • knowledge extraction • Knowledge Representation and Reasoning • Learning Paradigms • machine learning algorithms • multitask learning • nearest-neighbor search • Reinforcement Learning • social recommendation • supervised learning • Unsupervised Learning • Web mining
ISBN-10	3-662-44847-5 / 3662448475
ISBN-13	978-3-662-44847-2 / 9783662448472
Zustand	Neuware