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

The 9th International Conference on Discovery Science (DS 2006) was held in Barcelona, Spain, on 7-10 October 2006. The conference was collocated with the 17th International Conference on Algorithmic Learning Theory (ALT 2006). The two conferences shared the invited talks. This LNAI volume, containi...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Lavrač, Nada (Editor ), Todorovski, Ljupco (Editor ), Jantke, Klaus P. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Colección:Lecture Notes in Artificial Intelligence, 4265
Temas:
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.