Adams / Robardet / Siebes | Advances in Intelligent Data Analysis VIII | E-Book | sack.de
E-Book

E-Book, Englisch, 418 Seiten, eBook

Reihe: Information Systems and Applications, incl. Internet/Web, and HCI

Adams / Robardet / Siebes Advances in Intelligent Data Analysis VIII

8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009, Proceedings
2009
ISBN: 978-3-642-03915-7
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009, Proceedings

E-Book, Englisch, 418 Seiten, eBook

Reihe: Information Systems and Applications, incl. Internet/Web, and HCI

ISBN: 978-3-642-03915-7
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark



Adams / Robardet / Siebes Advances in Intelligent Data Analysis VIII jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


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.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.