Machine Learning and Knowledge Discovery in Databases, 2014 European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part I Lecture Notes in Artificial Intelligence Series
Coordonnateurs : Calders Toon, Esposito Floriana, Hüllermeier Eyke, Meo Rosa
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.
Date de parution : 09-2014
Ouvrage de 709 p.
15.5x23.5 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 52,74 €
Ajouter au panierThèmes de Machine Learning and Knowledge Discovery in Databases :
Mots-clés :
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