Editors:
- Covers the latest theoretical developments in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization
- Presents computational aspects and applications for data mining and visualization
- Gathers refereed papers presented at the 13th International Workshop WSOM+ 2019, held in Barcelona, Spain on 26–28 June 2019
Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 976)
Conference series link(s): WSOM: International Workshop on Self-Organizing Maps
Conference proceedings info: WSOM 2019.
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Table of contents (33 papers)
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Front Matter
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Self-organizing Maps: Theoretical Developments
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Front Matter
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Practical Applications of Self-Organizing Maps, Learning Vector Quantization and Clustering
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Front Matter
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Other Volumes
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Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization
About this book
This book gathers papers presented at the 13th International Workshop on Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization (WSOM+), which was held in Barcelona, Spain, from the 26th to the 28th of June 2019. Since being founded in 1997, the conference has showcased the state of the art in unsupervised machine learning methods related to the successful and widely used self-organizing map (SOM) method, and extending its scope to clustering and data visualization. In this installment of the AISC series, the reader will find theoretical research on SOM, LVQ and related methods, as well as numerous applications to problems in fields ranging from business and engineering to the life sciences. Given the scope of its coverage, the book will be of interest to machine learning researchers and practitioners in general and, more specifically, to those looking for the latest developments in unsupervised learning and data visualization.
Editors and Affiliations
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Department of Computer Science, UPC BarcelonaTech, Barcelona, Spain
Alfredo Vellido
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Knowledge Engineering and Machine Learning Group (KEMLG) at Intelligent Data Science and Artificial Intelligence Research Center, UPC BarcelonaTech, Barcelona, Spain
Karina Gibert
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Department of Automatic Control, UPC BarcelonaTech, Barcelona, Spain
Cecilio Angulo
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Departament d'Enginyeria Electrònica, Universitat de València, Burjassot, Spain
José David Martín Guerrero
Bibliographic Information
Book Title: Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization
Book Subtitle: Proceedings of the 13th International Workshop, WSOM+ 2019, Barcelona, Spain, June 26-28, 2019
Editors: Alfredo Vellido, Karina Gibert, Cecilio Angulo, José David Martín Guerrero
Series Title: Advances in Intelligent Systems and Computing
DOI: https://doi.org/10.1007/978-3-030-19642-4
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Softcover ISBN: 978-3-030-19641-7Published: 28 April 2019
eBook ISBN: 978-3-030-19642-4Published: 27 April 2019
Series ISSN: 2194-5357
Series E-ISSN: 2194-5365
Edition Number: 1
Number of Pages: XII, 342
Number of Illustrations: 48 b/w illustrations, 113 illustrations in colour