Discovery Science : 11th International Conference, DS 2008, Budapest, Hungary, October 13-16, 2008, Proceedings

by Boulicaut, Jean-Francois; Berthold, Michael R.; Horvath, Tamas

• ISBN13: 9783540884101
• ISBN10: 3540884106
• Format: Paperback
• Copyright: 2009-11-03
• Publisher: Springer Verlag

Summary

This book constitutes the refereed proceedings of the 11th International Conference on Discovery Science, DS 2008, held in Budapest, Hungary, in October 2008, co-located with the 19th International Conference on Algorithmic Learning Theory, ALT 2008.The 26 revised long papers presented together with 5 invited papers were carefully reviewed and selected from 58 submissions. The papers address all current issues in the area of development and analysis of methods for intelligent data analysis, knowledge discovery and machine learning, as well as their application to scientific knowledge discovery. The papers are organized in topical sections on learning, feature selection, associations, discovery processes, learning and chemistry, clustering, structured data, and text analysis.

Table of Contents

Invited Papers
On Iterative Algorithms with an Information Geometry Background	p. 1
Visual Analytics: Combining Automated Discovery with Interactive Visualizations	p. 2
Some Mathematics Behind Graph Property Testing	p. 15
Finding Total and Partial Orders from Data for Seriation	p. 16
Computational Models of Neural Representations in the Human Brain	p. 26
Learning
Unsupervised Classifier Selection Based on Two-Sample Test	p. 28
An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics	p. 40
Learning Model Trees from Data Streams	p. 52
Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees	p. 64
Ensemble-Trees: Leveraging Ensemble Power Inside Decision Trees	p. 76
A Comparison between Neural Network Methods for Learning Aggregate Functions	p. 88
Feature Selection
Smoothed Prediction of the Onset of Tree Stem Radius Increase Based on Temperature Patterns	p. 100
Feature Selection in Taxonomies with Applications to Paleontology	p. 112
Associations
Deduction Schemes for Association Rules	p. 124
Constructing Iceberg Lattices from Frequent Closures Using Generators	p. 136
Discovery Processes
Learning from Each Other	p. 148
Comparative Evaluation of Two Systems for the Visual Navigation of Encyclopedia Knowledge Spaces	p. 160
A Framework for Knowledge Discovery in a Society of Agents	p. 172
Learning and Chemistry
Active Learning for High Throughput Screening	p. 185
An Efficiently Computable Graph-Based Metric for the Classification of Small Molecules	p. 197
Mining Intervals of Graphs to Extract Characteristic Reaction Patterns	p. 210
Clustering
Refining Pairwise Similarity Matrix for Cluster Ensemble Problem with Cluster Relations	p. 222
Input Noise Robustness and Sensitivity Analysis to Improve Large Datasets Clustering by Using the GRID	p. 234
An Integrated Graph and Probability Based Clustering Framework for Sequential Data	p. 246
Cluster Analysis in Remote Sensing Spectral Imagery through Graph Representation and Advanced SOM Visualization	p. 259
Structured Data
Mining Unordered Distance-Constrained Embedded Subtrees	p. 272
Finding Frequent Patterns from Compressed Tree-Structured Data	p. 284
A Modeling Approach Using Multiple Graphs for Semi-Supervised Learning	p. 296
Text Analysis
String Kernels Based on Variable-Length-Don't-Care Patterns	p. 308
Unsupervised Spam Detection by Document Complexity Estimation	p. 319
A Probabilistic Neighbourhood Translation Approach for Non-standard Text Categorisation	p. 332
Author Index	p. 345
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