Discovery Science : 9th International Conference, DS 2006, Barcelona, Spain, October 7-10, 2006. Proceedings / edited by Ljup?o Todorovski, Nada Lavra?, Klaus P. Jantke.

Springer eBooks

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.

This book constitutes the refereed proceedings of the 9th International Conference on Discovery Science, DS 2006, held in Barcelona, Spain in October 2006, co-located with the 17th International Conference on Algorithmic Learning Theory, ALT 2006. The 23 revised long papers and the 18 revised regular papers presented together with 5 invited papers were carefully reviewed and selected from 87 submissions. The papers cover all issues in the area of automating scientific discovery or working on tools for supporting the human process of discovery in science. They address theoretical and methodological topics such as intelligent data analysis, knowledge discovery and machine learning, as well as their application to scientific knowledge discovery.

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