Editors:
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9853)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
Conference series link(s): ECML PKDD: Joint European Conference on Machine Learning and Knowledge Discovery in Databases
Conference proceedings info: ECML PKDD 2016.
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Table of contents (39 papers)
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Front Matter
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Demo Track Contributions
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Front Matter
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Industrial Track Contributions
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Front Matter
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Other Volumes
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Machine Learning and Knowledge Discovery in Databases
About this book
The three volume set LNAI 9851, LNAI 9852, and LNAI 9853 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2016, held in Riva del Garda, Italy, in September 2016. The 123 full papers and 16 short papers presented were carefully reviewed and selected from a total of 460 submissions. The papers presented focus on practical and real-world studies of machine learning, knowledge discovery, data mining; innovative prototype implementations or mature systems that use machine learning techniques and knowledge discovery processes in a real setting; recent advances at the frontier of machine learning and data mining with other disciplines. Part I and Part II of the proceedings contain the full papers of the contributions presented in the scientific track and abstracts of the scientific plenary talks. Part III contains the full papers of the contributions presented in the industrial track, short papers describing demonstration, the nectar papers, and the abstracts of the industrial plenary talks.
Keywords
- big data
- data mining
- information systems
- machine learning
- statistical methods
- applications
- artificial intelligence
- classification
- clustering
- enterprise applications
- graph mining
- large scale learning
- learning paradigms
- pattern mining
- probabilistic methods
- recommender systems
- sequence mining
- social media analysis
- supervised learning
- unsupervised learning
Editors and Affiliations
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Department of Computer Science, KU Leuven, Leuven, Belgium
Bettina Berendt
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Deloitte GmbH, München, Germany
Björn Bringmann
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Laboratoire Hubert Curien, Jean Monnet University, Saint-Etienne, France
Élisa Fromont
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Allianz SE, Munich, Germany
Gemma Garriga
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Max-Planck-Institute for Informatics, Saarbrücken, Germany
Pauli Miettinen
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Aalto University School of Science, Espoo, Finland
Nikolaj Tatti
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Siemens AG & Lud. Max. Univ. of Munich, Munich, Germany
Volker Tresp
Bibliographic Information
Book Title: Machine Learning and Knowledge Discovery in Databases
Book Subtitle: European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part III
Editors: Bettina Berendt, Björn Bringmann, Élisa Fromont, Gemma Garriga, Pauli Miettinen, Nikolaj Tatti, Volker Tresp
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-46131-1
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2016
Softcover ISBN: 978-3-319-46130-4Published: 03 September 2016
eBook ISBN: 978-3-319-46131-1Published: 02 September 2016
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XXII, 307
Number of Illustrations: 119 b/w illustrations
Topics: Data Mining and Knowledge Discovery, Artificial Intelligence, Pattern Recognition, Information Storage and Retrieval, Database Management, Information Systems Applications (incl. Internet)