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Advances in Self-Organizing Maps [electronic resource] : 9th International Workshop, WSOM 2012 Santiago, Chile, December 12-14, 2012 Proceedings / edited by Pablo A. Est�evez, Jos�e C. Pr�incipe, Pablo Zegers.

Contributor(s): Est�evez, Pablo A [editor.] | Pr�incipe, Jos�e C [editor.] | Zegers, Pablo [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Advances in Intelligent Systems and Computing: 198Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: XIV, 364 p. 133 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642352300.Subject(s): Engineering | Artificial intelligence | Computational intelligence | Complexity, Computational | Engineering | Computational Intelligence | Complexity | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Nonlinear Analysis and Time Series -- Text Mining and Language Processing -- Applications of Data Mining and Analysis.
In: Springer eBooksSummary: 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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Nonlinear Analysis and Time Series -- Text Mining and Language Processing -- Applications of Data Mining and Analysis.

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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