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Advances in Self-Organizing Maps

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Cover of 'Advances in Self-Organizing Maps'

Table of Contents

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    Book Overview
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    Chapter 1 Batch-Learning Self-Organizing Map for Predicting Functions of Poorly-Characterized Proteins Massively Accumulated
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    Chapter 2 Incremental Unsupervised Time Series Analysis Using Merge Growing Neural Gas
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    Chapter 3 Clustering Hierarchical Data Using Self-Organizing Map: A Graph-Theoretical Approach
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    Chapter 4 Time Series Clustering for Anomaly Detection Using Competitive Neural Networks
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    Chapter 5 Fault Prediction in Aircraft Engines Using Self-Organizing Maps
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    Chapter 6 Incremental Figure-Ground Segmentation Using Localized Adaptive Metrics in LVQ
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    Chapter 7 Application of Supervised Pareto Learning Self Organizing Maps and Its Incremental Learning
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    Chapter 8 Gamma SOM for Temporal Sequence Processing
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    Chapter 9 Fuzzy Variant of Affinity Propagation in Comparison to Median Fuzzy c-Means
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    Chapter 10 Clustering with Swarm Algorithms Compared to Emergent SOM
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    Chapter 11 Cartograms, Self-Organizing Maps, and Magnification Control
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    Chapter 12 Concept Mining with Self-Organizing Maps for the Semantic Web
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    Chapter 13 Advances in Self-Organizing Maps
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    Chapter 14 Early Recognition of Gesture Patterns Using Sparse Code of Self-Organizing Map
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    Chapter 15 Bag-of-Features Codebook Generation by Self-Organisation
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    Chapter 16 On the Quantization Error in SOM vs. VQ: A Critical and Systematic Study
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    Chapter 17 Approaching the Time Dependent Cocktail Party Problem with Online Sparse Coding Neural Gas
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    Chapter 18 Career-Path Analysis Using Optimal Matching and Self-Organizing Maps
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    Chapter 19 Network-Structured Particle Swarm Optimizer with Various Topology and Its Behaviors
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    Chapter 20 Representing Semantic Graphs in a Self-Organizing Map
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    Chapter 21 Analytic Comparison of Self-Organising Maps
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    Chapter 22 Modeling the Bilingual Lexicon of an Individual Subject
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    Chapter 23 Self-Organizing Maps with Non-cooperative Strategies (SOM-NC)
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    Chapter 24 Analysis of Parliamentary Election Results and Socio-Economic Situation Using Self-Organizing Map
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    Chapter 25 Line Image Classification by NG×SOM: Application to Handwritten Character Recognition
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    Chapter 26 Self-Organization of Tactile Receptive Fields: Exploring Their Textural Origin and Their Representational Properties
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    Chapter 27 Visualization by Linear Projections as Information Retrieval
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    Chapter 28 Analyzing Domestic Violence with Topographic Maps: A Comparative Study
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    Chapter 29 On the Finding Process of Volcano-Domain Ontology Components Using Self-Organizing Maps
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    Chapter 30 Elimination of Useless Neurons in Incremental Learnable Self-Organizing Map
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    Chapter 31 Hierarchical PCA Using Tree-SOM for the Identification of Bacteria
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    Chapter 32 Optimal Combination of SOM Search in Best-Matching Units and Map Neighborhood
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    Chapter 33 Sparse Linear Combination of SOMs for Data Imputation: Application to Financial Database
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    Chapter 34 Towards Semi-supervised Manifold Learning: UKR with Structural Hints
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    Chapter 35 Construction of a General Physical Condition Judgment System Using Acceleration Plethysmogram Pulse-Wave Analysis
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    Chapter 36 Top-Down Control of Learning in Biological Self-Organizing Maps
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    Chapter 37 Functional Principal Component Learning Using Oja’s Method and Sobolev Norms
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    Chapter 38 A Computational Framework for Nonlinear Dimensionality Reduction and Clustering
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    Chapter 39 The Exploration Machine – A Novel Method for Data Visualization
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    Chapter 40 Generalized Self-Organizing Mixture Autoregressive Model
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    Chapter 41 An SOM-Hybrid Supervised Model for the Prediction of Underlying Physical Parameters from Near-Infrared Planetary Spectra
Attention for Chapter 39: The Exploration Machine – A Novel Method for Data Visualization
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Citations

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Chapter title
The Exploration Machine – A Novel Method for Data Visualization
Chapter number 39
Book title
Advances in Self-Organizing Maps
Published by
Springer, Berlin, Heidelberg, June 2009
DOI 10.1007/978-3-642-02397-2_39
Book ISBNs
978-3-64-202396-5, 978-3-64-202397-2
Authors

Axel Wismüller, Wismüller, Axel

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 25%
Student > Ph. D. Student 2 25%
Student > Doctoral Student 1 13%
Student > Bachelor 1 13%
Researcher 1 13%
Other 1 13%
Readers by discipline Count As %
Business, Management and Accounting 2 25%
Computer Science 2 25%
Agricultural and Biological Sciences 1 13%
Physics and Astronomy 1 13%
Social Sciences 1 13%
Other 1 13%