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.
Ⅰ 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 Ⅱ 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 …… Ⅲ Regualar Papers Author Index
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