Riassunto
This book constitutes the refereed proceedings of the 8th International Conference on Intelligent Data Analysis, IDA 2009, held in Lyon, France, August 31 September 2, 2009.
The 33 revised papers, 18 full oral presentations and 15 poster and short oral presentations, presented were carefully reviewed and selected from almost 80 submissions. All current aspects of this interdisciplinary field are addressed; for example interactive tools to guide and support data analysis in complex scenarios, increasing availability of automatically collected data, tools that intelligently support and assist human analysts, how to control clustering results and isotonic classification trees. In general the areas covered include statistics, machine learning, data mining, classification and pattern recognition, clustering, applications, modeling, and interactive dynamic data visualization.
Contenuti
Invited Papers.- Intelligent Data Analysis in the 21st Century.- Analyzing the Localization of Retail Stores with Complex Systems Tools.- Selected Contributions 1 (Long Talks).- Change (Detection) You Can Believe in: Finding Distributional Shifts in Data Streams.- Exploiting Data Missingness in Bayesian Network Modeling.- DEMScale: Large Scale MDS Accounting for a Ridge Operator and Demographic Variables.- How to Control Clustering Results? Flexible Clustering Aggregation.- Compensation of Translational Displacement in Time Series Clustering Using Cross Correlation.- Context-Based Distance Learning for Categorical Data Clustering.- Semi-supervised Text Classification Using RBF Networks.- Improving k-NN for Human Cancer Classification Using the Gene Expression Profiles.- Subgroup Discovery for Test Selection: A Novel Approach and Its Application to Breast Cancer Diagnosis.- Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases.- Leveraging Call Center Logs for Customer Behavior Prediction.- Condensed Representation of Sequential Patterns According to Frequency-Based Measures.- ART-Based Neural Networks for Multi-label Classification.- Two-Way Grouping by One-Way Topic Models.- Selecting and Weighting Data for Building Consensus Gene Regulatory Networks.- Incremental Bayesian Network Learning for Scalable Feature Selection.- Feature Extraction and Selection from Vibration Measurements for Structural Health Monitoring.- Zero-Inflated Boosted Ensembles for Rare Event Counts.- Selected Contributions 2 (Short Talks).- Mining the Temporal Dimension of the Information Propagation.- Adaptive Learning from Evolving Data Streams.- An Application of Intelligent Data Analysis Techniques to a Large Software Engineering Dataset.- Which Distance for the Identification and the Differentiation of Cell-Cycle Expressed Genes?.- Ontology-Driven KDD Process Composition.- Mining Frequent Gradual Itemsets from Large Databases.- Selecting Computer Architectures by Means of Control-Flow-Graph Mining.- Visualization-Driven Structural and Statistical Analysis of Turbulent Flows.- Distributed Algorithm for Computing Formal Concepts Using Map-Reduce Framework.- Multi-Optimisation Consensus Clustering.- Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences.- Measure of Similarity and Compactness in Competitive Space.- Bayesian Solutions to the Label Switching Problem.- Efficient Vertical Mining of Frequent Closures and Generators.- Isotonic Classification Trees.
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