Call for papers




WSOM+ Invites contributions related to the theoretical and methodological aspects of Unsupervised learning, Self-Organizing Maps, Learning Vector Quantization, Clustering, Data Visualization and closely related topics, including but not limited to:

· Data analysis and visualization
· Clustering and visualization performance metrics
· Time series analysis and signal processing
· Mathematical approaches including information theory, mathematical statistics and statistical Machine Learning
· Software and hardware implementations
· Architectural solutions including hierarchical and growing networks, ensemble models and special metrics
· Unsupervised feature selection, extraction and data pre-processing.
· Interpretable and explainable models
· Large-scaale data analysis (Big Data)
· Unsupervised models in computational neuroscience
· Models, experimental investigations and applications of autonomous mental development.

We also call for and encourage scientific and application-oriented papers that demonstrate the use of the aforementioned methods and models in different areas including but not limited to:

· Data mining, including stream mining and process mining
· Pattern recognition
· Knowledge management
· Business intelligence and financial analysis
· Anomaly detection and outlier analysis
· Industrial applications
· Scientific applications
· Bioinformatics, biostatistics and applications in biomedicine and healthcare
· Telecommunications
· Transport optimization
· Cognitive modeling
· Language modeling
· Robotics and intelligent systems
· Image processing and vision
· Speech processing and text and document analysis


The WSOM+ 2019 proceedings will be published as a book in Springer’s Advances in Intelligent Systems and Computing (AISC) series 

NEWS: Selected papers of WSOM+2019 will be invited to a special issue of SpringerNature’s Neural Computing & Applications

Instructions for authors can be found in the Submission section.