Machine Learning and Knowledge Discovery in Databases
by Toon Calders, Floriana Esposito, Rosa Meo, Eyke Hüllermeier
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.
Paperback
English
Brand New
Publisher Description
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.
Back Cover
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.
Table of Contents
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.
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