[Apologies for multiple posting] Dear Colleague, We cordially invite you to submit a paper to the upcoming 14th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM+ 2022) July 6-8, 2022, Prague, Czechia https://wsom22.fel.cvut.cz/ Important Dates Paper submission: March 25, 2022 Notification of provisional acceptance: April 30, 2022 Camera-ready papers: May 15, 2022 Final acceptance: May 22, 2022 Topics: * 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-scale 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 Contact: Jan Faigl, Czech Technical University in Prague, Czechia faiglj@fel.cvut.cz Sincerely, WSOM+ 2022 Organizing Committee -- Tato zpráva byla zkontrolována na viry programem Avast Antivirus. https://www.avast.com/antivirus