Advances in Intelligent Data Analysis XIII

<p>Malware Phylogenetics Based on the Multiview Graphical Lasso.- Modeling stationary data by a class of generalized Ornstein-Uhlenbeck processes: the Gaussian case.- An approach to controlling the runtime for search based modularization of sequential source code check-ins Simple Pattern Spectrum Estimation for Fast Pattern Filtering with CoCoNAD.- From Sensor Readings to Predictions: on the Process of Developing Practical Soft Sensors.- Comparing Pre-Defined Software Engineering Metrics with Free-Text for the Prediction of Code Ripples.- ApiNATOMY: Towards Multiscale Views of Human Anatomy.- Granularity of co-Evolution Patterns in Dynamic Attributed Graphs.- Multi-user diverse recommendations through greedy vertex-angle maximization.- ERMiner: Sequential Rule Mining using Equivalence Classes.- Mining longitudinal epidemiological data to understand a reversible disorder.- The BioKET Biodiversity Data Warehouse: Data and Knowledge Integration and Extraction.- Using Time-Sensitive Rooted PageRank to Detect Hierarchical Social Relationships.- Modeling daily profiles of solar global radiation using statistical and data mining techniques.- Model-based Time Series Classification.- Fast simultaneous clustering and feature selection for binary data.- Identifying Bilingual Segments for Translation Generation.- Instant Exceptional Model Mining using Weighted Controlled Pattern Sampling.- Resampling approaches to improve news importance prediction.- An Incremental Probabilistic Model to Predict Bus Bunching in Real-Time.- Mining Representative Frequent Patterns in a Hierarchy of Contexts.- A Deep Interpretation of Classifier Chains.- A nonparametric mixture model for personalizing web search.- Widened KRIMP: Better Performance Through Diverse Parallelism.- Finding the Intrinsic Patterns in a Collection of Time Series.- A Spatio-Temporal Bayesian Network Approach for Revealing Functional Ecological Networks in Fisheries.- Extracting Predictive Models from Marked-Up Free-Text Documents at The Royal Botanic Gardens, Kew, London.- Detecting Localised Anomalous Behaviour in a Computer Network.</p>