The 11th International Conference on Discovery Science Hotel Budapest, Budapest, Hungary October 13 - 16, 2008

Time Schedule The conference is co-located with ALT 2008 (19th International Conference on Agorithmic Theory). It starts on Monday, October 13th, with two tutorials, scheduled as follows: 13:30-15:30: Tutorial 1 Saso Dzeroski: Constraint-Based Data Mining and Inductive Queries 15:30-16:00: Coffee Break 16:00-18:00: Tutorial 2 João Gama: Mining from Data Streams: Issues and Challenges 18:30-20:00: Steering Committee Meeting The table below presents the schedule for the other three days of the conference. Note that further info about the invited talks can be found on the Invited Talks page. Time Tuesday, 14 October Wednesday, 15 October Thursday, 16 October 09:00-10:00 Morning Invited Talks Heikki Mannila Finding Total and Partial Orders from Data for Seriation László Lovász Some Mathematics behind Graph Property Testing Imre Csiszár On Iterative Algorithms with an Information Geometry Background 10:00-10:15 Coffee Break 10:15-11:30 Learning 1 Discovery Processes Structured Data Timo Aho, Tapio Elomaa and Jussi Kujala Unsupervised Classifier Selection Based on Two-Sample Test Frederik Janssen and Johannes Furnkranz An Empirical Investigation of the Trade-Off Between Consistency and Coverage in Rule Learning Heuristics Albrecht Zimmermann Ensemble-Trees: Leveraging Ensemble Power inside Decision Trees Gauvain Bourgne and Vincent Corruble A Framework for Knowledge Discovery in a Society of Agents Christopher Dartnell, Eric Martin, and Jean Sallantin Learning from each other Wolfgang Kienreich and Peter Kraker Comparative Evaluation of Two Systems for the Visual Navigation of Encyclopedia Knowledge Spaces Fedja Hadzic, Henry Tan, and Tharam Dillon Mining Unordered Distance-constrained Embedded Subtrees Akihiko Izutani and Kuniaki Uehara A Modeling Approach using Multiple Graphs for Semi-Supervised Learning Seiji Murakami, Koichiro Doi, and Akihiro Yamamoto Finding Frequent Patterns from Compressed Tree-structured Data 11:30-11:40 Short Break 11:40-12:30 Feature Selection Association Rules Text Analysis Mikko Korpela, Harri Makinen, Mika Sulkava, Pekka Nojd, and Jaakko Hollmen Smoothed Prediction of the Onset of Tree Stem Radius Increase Based on Temperature Patterns Gemma C. Garriga, Antti Ukkonen, and Heikki Mannila Feature Selection in Taxonomies with Applications to Paleontology Jose L. Balcazar Deduction Schemes for Association Rules Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, and Robert Godin Constructing Iceberg Lattices from Frequent Closures Using Generators Ata Kaban A probabilistic neighbourhood translation approach for non-standard text categorisation Takashi Uenura, Daisuke Ikeda, and Hiroki Arimura Unsupervised Spam Detection by Document Complexity Estimation 12:30-14:00 Lunch Break 14:00-15:00 Afternoon Invited Talks Tom Mitchell Computational Models of Neural Representations in the Human Brain Daniel A. Keim Visual Analytics: Combining Automated Discovery with Interactive Visualizations Adjorn 15:00-15:10 Short Break 15:10-16:50 Learning 2 Clustering Beau Piccart, Jan Struyf and Hendrik Blockeel Empirical Asymmetric Selective Transfer in Multi-Objective Decision Trees Werner Uwents and Hendrik Blockeel A comparison between neural network methods for learning aggregate functions Elena Ikonomovska and Joao Gama Learning Model Trees from Data Streams Kazuyuki Narisawa, Hideo Bannai, Kohei Hatano, Shunsuke Inenaga and Masayuki Takeda String Kernels Based on Variable-Length-Don't-Care Patterns Natthakan Iam-on, Tossapon Boongoon, and Simon Garrett Refining Pairwise Similarity Matrix for Cluster Ensemble Problem with Cluster Relations Haytham Elghazel, Tetsuya Yoshida, and Mohand-Said Hacid An Integrated Graph and Probability Based Clustering Framework for Sequential Data Alberto Faro, Daniela Giordano, and Francesco Maiorana Input noise robustness and sensitivity analysis to improve large datasets clustering by using the GRID Kadim Tasdemir and Erzsebet Merenyi Cluster analysis in remote sensing spectral imagery through graph representation and advanced SOM visualization 16:50-17:10 Coffee Break 17:10-18:50 Learning and Chemistry Kurt De Grave, Jan Ramon, and Luc De Raedt Active Learning for High Throughput Screening Frederic Pennerath, Geraldine Polaillon, and Amedeo Napoli Mining Graph Intervals to Extract Characteristic Reaction Patterns Leander Schietgat, Jan Ramon, Maurice Bruynooghe, and Hendrik Blockeel An Efficiently Computable Graph-based Metric for the Classification of Small Molecules 19:00- Business Meeting Banquet