Advances in Self-Organizing Maps: 7th International Workshop, WSOM 2009, St. Augustine, Florida, June 8-10, 2009. ProceedingsJ.C. Principe, Risto Miikkulainen Springer, 4 juin 2009 - 374 pages th These proceedings contain refereed papers presented at the 7 WSOM held at the Casa Monica Hotel, St. Augustine, Florida, June 8–10, 2009. We designed the wo- shop to serve as a regular forum for researchers in academia and industry who are interested in the exciting field of self-organizing maps (SOM). The program includes excellent examples of the use of SOM in many areas of social sciences, economics, computational biology, engineering, time series analysis, data visualization and c- puter science as well a vibrant set of theoretical papers that keep pushing the envelope of the original SOM. Our deep appreciation is extended to Teuvo Kohonen and Ping Li for the plenary talks and Amaury Lendasse for the organization of the special sessions. Our sincere thanks go to the members of the Technical Committee and other reviewers for their excellent and timely reviews, and above all to the authors whose contributions made this workshop possible. Special thanks go to Julie Veal for her dedication and hard work in coordinating the many details necessary to put together the program and local arrangements. Jose C. Principe Risto Miikkulainen |
Table des matières
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| 10 | |
A GraphTheoretical Approach | 19 |
Time Series Clustering for Anomaly Detection Using Competitive Neural Networks | 28 |
Fault Prediction in Aircraft Engines Using SelfOrganizing Maps | 37 |
Incremental FigureGround Segmentation Using Localized Adaptive Metrics in LVQ | 45 |
Application of Supervised Pareto Learning Self Organizing Maps and Its Incremental Learning | 54 |
Gamma SOM for Temporal Sequence Processing | 63 |
SelfOrganizing Maps with Noncooperative Strategies SOMNC | 200 |
Analysis of Parliamentary Election Results and SocioEconomic Situation Using SelfOrganizing Map | 209 |
Application to Handwritten Character Recognition | 219 |
Exploring Their Textural Origin and Their Representational Properties | 228 |
Visualization by Linear Projections as Information Retrieval | 237 |
A Comparative Study | 246 |
On the Finding Process of VolcanoDomain Ontology Components Using SelfOrganizing Maps | 255 |
Elimination of Useless Neurons in Incremental Learnable SelfOrganizing Map | 264 |
Fuzzy Variant of Affinity Propagation in Comparison to Median Fuzzy cMeans | 72 |
Clustering with Swarm Algorithms Compared to Emergent SOM | 80 |
Cartograms SelfOrganizing Maps and Magnification Control | 89 |
Concept Mining with SelfOrganizing Maps for the Semantic Web | 98 |
ViSOM for Dimensionality Reduction in Face Recognition | 107 |
Early Recognition of Gesture Patterns Using Sparse Code of SelfOrganizing Map | 116 |
BagofFeatures Codebook Generation by SelfOrganisation | 124 |
A Critical and Systematic Study | 133 |
Approaching the Time Dependent Cocktail Party Problem with Online Sparse Coding Neural Gas | 145 |
CareerPath Analysis Using Optimal Matching and SelfOrganizing Maps | 154 |
NetworkStructured Particle Swarm Optimizer with Various Topology and Its Behaviors | 163 |
Representing Semantic Graphs in a SelfOrganizing Map | 172 |
Analytic Comparison of SelfOrganising Maps | 182 |
Modeling the Bilingual Lexicon of an Individual Subject | 191 |
Hierarchical PCA Using TreeSOM for the Identification of Bacteria | 272 |
Optimal Combination of SOM Search in BestMatching Units and Map Neighborhood | 281 |
Application to Financial Database | 290 |
UKR with Structural Hints | 298 |
Construction of a General Physical Condition Judgment System Using Acceleration Plethysmogram PulseWave Analysis | 307 |
TopDown Control of Learning in Biological SelfOrganizing Maps | 316 |
Functional Principal Component Learning Using Ojas Method and Sobolev Norms | 325 |
A Computational Framework for Nonlinear Dimensionality Reduction and Clustering | 334 |
The Exploration Machine A Novel Method for Data Visualization | 344 |
Generalized SelfOrganizing Mixture Autoregressive Model | 353 |
An SOMHybrid Supervised Model for the Prediction of Underlying Physical Parameters from NearInfrared Planetary Spectra | 362 |
| 372 | |
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Expressions et termes fréquents
1st-NGs adaptation algorithm analysis applied approach Berlin Heidelberg 2009 best matching c-means cartogram classification cluster codebook component Computer context data set defined distance ESOM evaluation experiments Exploration Machine frame function genome gesture grid Heidelberg hierarchical high-dimensional IEEE incremental learning input data input vector Isomap kernel Kohonen label linear Listeria LNCS machine learning method Miikkulainen Miikkulainen Eds mixing matrix neighborhood neighbors Neural Gas Neural Networks neurons NG×SOM node nonlinear nonlinear dimensionality reduction NS-PSO obtained ontology optimal Organizing Maps output parameters Pareto Particle Swarm Optimizer particles performance plethysmogram Proc projection proteins prototypes quantization error receptive field represent representation retrieval rms QE samples Self-Organizing Maps semantic sequences shown SOMs sparse code spectra Springer Springer-Verlag Berlin Heidelberg strategy structure temporal topographic topology training vectors units unsupervised unsupervised learning updated values variables variance Vibrio ViSOM visualization weight vector winner WSOM