Advances in Intelligent Data Analysis VIII 8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009. Proceedings / [electronic resource] :
edited by Niall M. Adams, Céline Robardet, Arno Siebes, Jean-François Boulicaut.
- Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
- XIII, 418 p. online resource.
- Lecture Notes in Computer Science, 5772 0302-9743 ; .
- Lecture Notes in Computer Science, 5772 .
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.
9783642039157
10.1007/978-3-642-03915-7 doi
Computer science.
Data structures (Computer science).
Data mining.
Information storage and retrieval systems.
Optical pattern recognition.
Bioinformatics.
Management information systems.
Computer Science.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
Pattern Recognition.
Data Structures.
Business Information Systems.
Computational Biology/Bioinformatics.
QA75.5-76.95
025.04
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.
9783642039157
10.1007/978-3-642-03915-7 doi
Computer science.
Data structures (Computer science).
Data mining.
Information storage and retrieval systems.
Optical pattern recognition.
Bioinformatics.
Management information systems.
Computer Science.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
Pattern Recognition.
Data Structures.
Business Information Systems.
Computational Biology/Bioinformatics.
QA75.5-76.95
025.04