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  • Produktbild: Discovery Science
  • Produktbild: Discovery Science

Discovery Science 9th International Conference, DS 2006, Barcelona, Spain, October 7-10, 2006, Proceedings

Aus der Reihe Lecture Notes in Artificial Intelligence

49,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.09.2006

Herausgeber

Nada Lavrač + weitere

Verlag

Springer Berlin

Seitenzahl

386

Maße (L/B/H)

23,5/15,5/2,2 cm

Gewicht

610 g

Auflage

2006

Sprache

Englisch

ISBN

978-3-540-46491-4

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.09.2006

Herausgeber

Verlag

Springer Berlin

Seitenzahl

386

Maße (L/B/H)

23,5/15,5/2,2 cm

Gewicht

610 g

Auflage

2006

Sprache

Englisch

ISBN

978-3-540-46491-4

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Discovery Science
  • Produktbild: Discovery Science
  • Invited Papers.- e-Science and the Semantic Web: A Symbiotic Relationship.- Data-Driven Discovery Using Probabilistic Hidden Variable Models.- Reinforcement Learning and Apprenticeship Learning for Robotic Control.- The Solution of Semi-Infinite Linear Programs Using Boosting-Like Methods.- Spectral Norm in Learning Theory: Some Selected Topics.- Long Papers.- Classification of Changing Regions Based on Temporal Context in Local Spatial Association.- Kalman Filters and Adaptive Windows for Learning in Data Streams.- Scientific Discovery: A View from the Trenches.- Optimal Bayesian 2D-Discretization for Variable Ranking in Regression.- Text Data Clustering by Contextual Graphs.- Automatic Water Eddy Detection in SST Maps Using Random Ellipse Fitting and Vectorial Fields for Image Segmentation.- Mining Approximate Motifs in Time Series.- Identifying Historical Period and Ethnic Origin of Documents Using Stylistic Feature Sets.- A New Family of String Classifiers Based on Local Relatedness.- On Class Visualisation for High Dimensional Data: Exploring Scientific Data Sets.- Mining Sectorial Episodes from Event Sequences.- A Voronoi Diagram Approach to Autonomous Clustering.- Itemset Support Queries Using Frequent Itemsets and Their Condensed Representations.- Strategy Diagram for Identifying Play Strategies in Multi-view Soccer Video Data.- Prediction of Domain-Domain Interactions Using Inductive Logic Programming from Multiple Genome Databases.- Clustering Pairwise Distances with Missing Data: Maximum Cuts Versus Normalized Cuts.- Analysis of Linux Evolution Using Aligned Source Code Segments.- Rule-Based Prediction of Rare Extreme Values.- A Pragmatic Logic of Scientific Discovery.- Change Detection with Kalman Filter and CUSUM.- Automatic Recognition of Landforms on Mars Using Terrain Segmentation and Classification.- A Multilingual Named Entity Recognition System Using Boosting and C4.5 Decision Tree Learning Algorithms.- Model-Based Estimation of Word Saliency in Text.- Regular Papers.- Learning Bayesian Network Equivalence Classes from Incomplete Data.- Interesting Patterns Extraction Using Prior Knowledge.- Visual Interactive Subgroup Discovery with Numerical Properties of Interest.- Contextual Ontological Concepts Extraction.- Experiences from a Socio-economic Application of Induction Trees.- Interpreting Microarray Experiments Via Co-expressed Gene Groups Analysis (CGGA).- Symmetric Item Set Mining Based on Zero-Suppressed BDDs.- Mathematical Models of Category-Based Induction.- Automatic Construction of Static Evaluation Functions for Computer Game Players.- Databases Reduction Simultaneously by Ordered Projection.- Mapping Ontologies in an Air Pollution Monitoring and Control Agent-Based System.- Information Theory and Classification Error in Probabilistic Classifiers.- Checking Scientific Assumptions by Modeling.- Incremental Algorithm Driven by Error Margins.- Feature Construction and ?-Free Sets in 0/1 Samples.- Visual Knowledge Discovery in Paleoclimatology with Parallel Coordinates.- A Novel Framework for Discovering Robust Cluster Results.- Gene Selection for Classifying Microarray Data Using Grey Relation Analysis.