Advances in intelligent data analysis VIII : 8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009 ; proceedings / Niall M. Adams [and others] (eds.).

By: (8th : International Symposium on Intelligent Data Analysis (8th : 2009 : Lyon, France)
Contributor(s): Adams, Niall M, 1968-
Material type: TextTextSeries: SerienbezeichnungLecture notes in computer science: 5772.Publisher: Berlin : Springer-Verlag, ©2009Description: 1 online resource (xiii, 418 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9783642039157; 3642039154Other title: IDA 2009Subject(s): Data mining -- Congresses | Mathematical statistics -- Data processing -- Congresses | Data mining | Mathematical statistics -- Data processing | Informatique | Data mining | Mathematical statistics -- Data processing | DatenanalyseGenre/Form: Electronic books. | Conference papers and proceedings. Additional physical formats: Print version:: Advances in intelligent data analysis VIII.DDC classification: 006.3/12 LOC classification: QA76.9.D343 | I584 2009Other classification: 54.62 | TP274-1 | SS 4800 | DAT 703f | MAT 620f Online resources: Click here to access online
Contents:
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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International conference proceedings.

Includes bibliographical references and index.

Print version record.

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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