Advances in Intelligent Data Analysis XIII -

. .

Résumé :
This book constitutes the refereed conference proceedings of the 13th International Conference on Intelligent Data Analysis, which was held in October/November 2014 in Leuven, Belgium. The 33 revised full papers together with 3 invited papers were carefully reviewed and selected from 70 submissions handling all kinds of modeling and analysis methods, irrespective of discipline. The papers cover all aspects of intelligent data analysis, including papers on intelligent support for modeling and analyzing data from complex, dynamical systems.

Sommaire:

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.