Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Database Management, General Computing
Cover of the book Machine Learning and Knowledge Discovery in Databases by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319462271
Publisher: Springer International Publishing Publication: September 3, 2016
Imprint: Springer Language: English
Author:
ISBN: 9783319462271
Publisher: Springer International Publishing
Publication: September 3, 2016
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer International Publishing

Cover of the book Aurora 7 by
Cover of the book Purgatory by
Cover of the book Design Thinking Research by
Cover of the book Translating Molecules into Medicines by
Cover of the book Cross-Cultural Design by
Cover of the book Computational Photonic Sensors by
Cover of the book Introduction to Frame Analysis by
Cover of the book Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation by
Cover of the book The Social Psychology of Intractable Conflicts by
Cover of the book Interpretations of Luxury by
Cover of the book Current Management of Venous Diseases by
Cover of the book Methodologies in Peace Psychology by
Cover of the book Interdisciplinary Research and Trans-disciplinary Validity Claims by
Cover of the book Particle Interactions in High-Temperature Plasmas by
Cover of the book Cell Biology of Herpes Viruses by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy