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130626 ||| eng |
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|a 9783642352300
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| 100 |
1 |
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|a Estévez, Pablo A.
|e [editor]
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| 245 |
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|a Advances in Self-Organizing Maps
|h Elektronische Ressource
|b 9th International Workshop, WSOM 2012 Santiago, Chile, December 12-14, 2012 Proceedings
|c edited by Pablo A. Estévez, José C. Príncipe, Pablo Zegers
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| 250 |
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|a 1st ed. 2013
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| 260 |
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|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 2013, 2013
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| 300 |
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|a XIV, 364 p. 133 illus
|b online resource
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| 505 |
0 |
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|a Nonlinear Analysis and Time Series -- Text Mining and Language Processing -- Applications of Data Mining and Analysis
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| 653 |
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|a Computational intelligence
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| 653 |
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|a Applied Dynamical Systems
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Computational Intelligence
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| 653 |
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|a Nonlinear theories
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Dynamics
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| 700 |
1 |
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|a Príncipe, José C.
|e [editor]
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| 700 |
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|a Zegers, Pablo
|e [editor]
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
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|a Advances in Intelligent Systems and Computing
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| 028 |
5 |
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|a 10.1007/978-3-642-35230-0
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-642-35230-0?nosfx=y
|x Verlag
|3 Volltext
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|a 006.3
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| 520 |
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|a Self-organizing maps (SOMs) were developed by Teuvo Kohonen in the early eighties. Since then more than 10,000 works have been based on SOMs. SOMs are unsupervised neural networks useful for clustering and visualization purposes. Many SOM applications have been developed in engineering and science, and other fields. This book contains refereed papers presented at the 9th Workshop on Self-Organizing Maps (WSOM 2012) held at the Universidad de Chile, Santiago, Chile, on December 12-14, 2012. The workshop brought together researchers and practitioners in the field of self-organizing systems. Among the book chapters there are excellent examples of the use of SOMs in agriculture, computer science, data visualization, health systems, economics, engineering, social sciences, text and image analysis, and time series analysis. Other chapters present the latest theoretical work on SOMs as well as Learning Vector Quantization (LVQ) methods
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