Online-Ressource | |
Titel: | Machine Learning and Data Mining in Pattern Recognition |
Titelzusatz: | 12th International Conference, MLDM 2016, New York, NY, USA, July 16-21, 2016, Proceedings |
Mitwirkende: | Perner, Petra [Hrsg.] |
Verf.angabe: | edited by Petra Perner |
Verlagsort: | Cham |
Verlag: | Springer |
Jahr: | 2016 |
Umfang: | Online-Ressource (XIII, 807 p. 291 illus, online resource) |
Gesamttitel/Reihe: | Lecture Notes in Computer Science ; 9729 |
Lecture Notes in Artificial Intelligence ; 9729 | |
SpringerLink : Bücher | |
Springer eBook Collection : Computer Science | |
ISBN: | 978-3-319-41920-6 |
Abstract: | This book constitutes the refereed proceedings of the 12th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2016, held in New York, NY, USA in July 2016. The 58 regular papers presented in this book were carefully reviewed and selected from 169 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining |
Classification -- Clustering -- Association rule -- Pattern mining -- Image mining.-Text mining -- Video mining -- Web mining | |
DOI: | doi:10.1007/978-3-319-41920-6 |
URL: | Volltext: https://doi.org/10.1007/978-3-319-41920-6 |
Cover: https://swbplus.bsz-bw.de/bsz473971399cov.jpg | |
DOI: https://doi.org/10.1007/978-3-319-41920-6 | |
Schlagwörter: | (s)Data Mining / (s)Maschinelles Lernen / (s)Mustererkennung / (s)Automatische Klassifikation |
Datenträger: | Online-Ressource |
Sprache: | eng |
Reproduktion: | Druckausg |
Printed edition | |
K10plus-PPN: | 1657718468 |
Verknüpfungen: | → Übergeordnete Aufnahme |
Lokale URL UB: | Zum Volltext |
Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg | |
Bestellen/Vormerken für Benutzer des Klinikums Mannheim Eigene Kennung erforderlich | |
Bibliothek/Idn: | UW / m3398821634 |
Lokale URL Inst.: | Zum Volltext |