2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM)

We invite contributions related to the theoretical and methodological aspects of Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization approaches and closely related topics including :

• Data analysis and data visualization

• Temporal and incremental data mining

• Various mathematical approaches including information theory and mathematical statistics

• Software and hardware implementations

• Architectural solutions including hierarchical and growing networks, ensemble models and special metrics

• Neuro-cognitive studies that compare modeling and empirical results at different levels

• Models, experimental investigations and applications of autonomous mental development.

We also call for scientific and practice-oriented papers that demonstrate the use of Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization approaches in different application areas including but not limited to :

• Data mining

• Pattern recognition

• Signal processing

• Knowledge management

• Time series processing

• Modeling dynamic phenomena

• Anomalies and fault detection

• Industrial applications

• Bioinformatics

• Biomedical applications

• Telecommunications

• Financial analysis

• Applications for transport optimization

• Cognitive modeling

• Language modeling

• Robotics and intelligent systems

• Image processing and vision

• Speech processing

• Text and document analysis