Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part I

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.

List 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.

Product details

• Assisted by: Toon Calders (Editor), Floriana Esposito (Editor), Eyke Hüllermeier (Editor), Rosa Meo (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 12.09.2014
• EAN: 9783662448472
• ISBN: 978-3-662-44847-2
• No. of pages: 709
• Dimensions: 167 mm x 36 mm x 239 mm
• Weight: 1124 g
• Illustrations: XLIV, 709 p. 183 illus.
• Series: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; C, Künstliche Intelligenz, Data Mining, Artificial Intelligence, Mustererkennung, Data Warehousing, Informationsrückgewinnung, Information Retrieval, Wissensbasierte Systeme, Expertensysteme, computer science, Information Retrieval, Supervised Learning, Unsupervised Learning, Reinforcement Learning, pattern recognition, Data Mining and Knowledge Discovery, Automated Pattern Recognition, Expert systems / knowledge-based systems, Information Storage and Retrieval, Web Mining, machine learning algorithms, social recommendation, nearest-neighbor search, learning paradigms, multitask learning