The 'Neural' Phonetic Typewriter
Computer
Neural Networks
Visual Explorations in Finance
Visual Explorations in Finance
Self-Organizing Maps
A Method for Temporal Knowledge Conversion
IDA '99 Proceedings of the Third International Symposium on Advances in Intelligent Data Analysis
Recursive self-organizing maps
Neural Networks - New developments in self-organizing maps
Semiology of graphics
A Visualization System for Space-Time and Multivariate Patterns (VIS-STAMP)
IEEE Transactions on Visualization and Computer Graphics
A taxonomy of Self-organizing Maps for temporal sequence processing
Intelligent Data Analysis
A Nonlinear Mapping for Data Structure Analysis
IEEE Transactions on Computers
Neurocomputing
Unsupervised recursive sequence processing
Neurocomputing
Visualizing temporal cluster changes using Relative Density Self-Organizing Maps
Knowledge and Information Systems - Special Issue:Best Papers from the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2008);Guest Editors: Takashi Washio, Einoshin Suzuki and Kai Ming Ting
Fuzzy clustering of the self-organizing map: some applications on financial time series
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
International Journal of Intelligent Systems in Accounting and Finance Management
Financial performance analysis of European banks using a fuzzified self-organizing map
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
Visualization of cluster changes by comparing self-organizing maps
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
A self-organizing map for adaptive processing of structured data
IEEE Transactions on Neural Networks
A Framework For State Transitions On The Self-Organizing Map: Some Temporal Financial Applications
International Journal of Intelligent Systems in Accounting and Finance Management
Space-in-time and time-in-space self-organizing maps for exploring spatiotemporal patterns
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
Decomposing the global financial crisis: A Self-Organizing Time Map
Pattern Recognition Letters
Letters: Clustering of the Self-Organizing Time Map
Neurocomputing
Hi-index | 0.01 |
This paper adopts and adapts Kohonen's standard self-organizing map (SOM) for exploratory temporal structure analysis. The self-organizing time map (SOTM) implements SOM-type learning to one-dimensional arrays for individual time units, preserves the orientation with short-term memory and arranges the arrays in an ascending order of time. The two-dimensional representation of the SOTM attempts thus twofold topology preservation, where the horizontal direction preserves time topology and the vertical direction data topology. This enables discovering the occurrence and exploring the properties of temporal structural changes in data. For representing qualities and properties of SOTMs, we adapt measures and visualizations from the standard SOM paradigm, as well as introduce a measure of temporal structural changes. The functioning of the SOTM, and its visualizations and quality and property measures, are illustrated on artificial toy data. The usefulness of the SOTM in a real-world setting is shown on poverty, welfare and development indicators.