From data to models and back : 9th International Symposium, DataMod 2020, Virtual Event, October 20, 2020, Revised Selected Papers / Juliana Bowles, Giovanna Broccia, Mirco Nanni (eds.)
Synthesis and Pruning as a Dynamic Compression Strategy for Efficient Deep Neural Networks -- Exploring Graph-Based Neural Networks for Automatic Brain Tumor Segmentation -- STDI-Net: Spatial-Temporal Network with Dynamic Interval Mapping for Bike Sharing Demand Prediction -- A Simulation-Based Approach for the Behavioural Analysis of Cancer Pathways -- Discovering the Impact of Notifications on Social Network Addiction -- A Simulation Study on Demand Disruptions and Limited Resources for Healthcare Provision -- A Formal Model for Emulating the Generation of Human Knowledge in Semantic Memory -- Analysis of COVID-19 data with PRISM: Parameter Estimation and SIR Modelling -- A Formal Model for the Simulation and Analysis of Early Biofilm Formation -- Query Rewriting On Path Views Without Integrity Constraints -- Evaluating Trace Encoding Methods in Process Mining -- Semantic Annotations in Clinical Guidelines -- Deriving Performance Measures of Workflow in Radiation Therapy from Real-Time Data -- Handshape Classification in a Reverse Dictionary of Sign Languages for the Deaf
Summary
This book constitutes the refereed proceedings of the 9th International Symposium on From Data Models and Back, DataMod 2020, held virtually, in October 2020. The 11 full papers and 3 short papers presented in this book were selected from 19 submissions. The papers are grouped in these topical sections: machine learning; simulation-based approaches, and data mining and processing related approaches
