5. IDA 2003: Berlin, Germany

Machine Learning

• A. J. Feelders, Martijn Pardoel:
  Pruning for Monotone Classification Trees. 1-12
  
• Eyke Hüllermeier:
  Regularized Learning with Flexible Constraints. 13-24
  
• Michael Kockelkorn, Andreas Lüneburg, Tobias Scheffer:
  Learning to Answer Emails. 25-35
  
• Axel Großmann, Matthias Wendt, Jeremy Wyatt:
  A Semi-supervised Method for Learning the Structure of Robot Environment Interactions. 36-47
  
• Ljupco Todorovski, Saso Dzeroski:
  Using Domain Specific Knowledge for Automated Modeling. 48-59
  
• Tony Lindgren, Henrik Boström:
  Resolving Rule Conflicts with Double Induction. 60-67
  
• Chi-Chun Huang, Hahn-Ming Lee:
  A Novel Partial-Memory Learning Algorithm Based on Grey Relational Structure. 68-75
  
• Thomas R. Gabriel, Michael R. Berthold:
  Constructing Hierarchical Rule Systems. 76-87
  
• In-Cheol Kim, Soon-Hee Myoung:
  Text Categorization Using Hybrid Multiple Model Schemes. 88-99
  

Probability and Topology

• Allan Tucker, Xiaohui Liu:
  Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies. 100-110
  
• V. Robins, Jennifer Abernethy, N. Rooney, Elizabeth Bradley:
  Topology and Intelligent Data Analysis. 111-122
  
• Giulianella Coletti, Romano Scozzafava:
  Coherent Conditional Probability as a Measure of Information of the Relevant Conditioning Events. 123-133
  
• Paul R. Cohen, Charles A. Sutton:
  Very Predictive Ngrams for Space-Limited Probabilistic Models. 134-142
  
• Víctor Robles, Pedro Larrañaga, José M. Peña Sánchez, Ernestina Menasalvas Ruiz, María S. Pérez:
  Interval Estimation Naïve Bayes. 143-154
  
• Peter Mutschke:
  Mining Networks and Central Entities in Digital Libraries. A Graph Theoretic Approach Applied to Co-author Networks. 155-166
  

Classification and Pattern Recognition

• Peter Geibel, Ulf Brefeld, Fritz Wysotzki:
  Learning Linear Classifiers Sensitive to Example Dependent and Noisy Costs. 167-178
  
• Boris Kryzhanovsky, Leonid B. Litinskii, Anatoly B. Fonarev:
  An Effective Associative Memory for Pattern Recognition. 179-186
  
• Axel E. Bernal, Karen Hospevian, Tayfun Karadeniz, Jean-Louis Lassez:
  Similarity Based Classification. 187-197
  
• Fernando Berzal Galiano, Juan C. Cubero, Nicolás Marín, Daniel Sánchez:
  Numerical Attributes in Decision Trees: A Hierarchical Approach. 198-207
  
• Igor Fischer:
  Similarity-Based Neural Networks for Applications in Computational Molecular Biology. 208-218
  
• Petr Savický, Johannes Fürnkranz:
  Combining Pairwise Classifiers with Stacking. 219-229
  
• Branko Kavsek, Nada Lavrac, Viktor Jovanoski:
  APRIORI-SD: Adapting Association Rule Learning to Subgroup Discovery. 230-241
  
• Mihai Oltean, Crina Grosan:
  Solving Classification Problems Using Infix Form Genetic Programming. 242-253
  

Clustering

• Frank Klawonn, Frank Höppner:
  What Is Fuzzy about Fuzzy Clustering? Understanding and Improving the Concept of the Fuzzifier. 254-264
  
• Allou Samé, Christophe Ambroise, Gérard Govaert:
  A Mixture Model Approach for Binned Data Clustering. 265-274
  
• János Abonyi, Balazs Feil, Sandor Z. Németh, Peter Arva:
  Fuzzy Clustering Based Segmentation of Time-Series. 275-285
  
• Peter Merz:
  An Iterated Local Search Approach for Minimum Sum-of-Squares Clustering. 286-296
  
• Chun-Hung Tzeng, Fu-Shing Sun:
  Data Clustering in Tolerance Space. 297-306
  
• Hanan Ayad, Mohamed S. Kamel:
  Refined Shared Nearest Neighbors Graph for Combining Multiple Data Clusterings. 307-318
  
• Dimitrios Katsaros, Alexandros Nanopoulos, Murat Karakaya, Gökhan Yavas, Özgür Ulusoy, Yannis Manolopoulos:
  Clustering Mobile Trajectories for Resource Allocation in Mobile Environments. 319-329
  
• Carla S. Möller-Levet, Frank Klawonn, Kwang-Hyun Cho, Olaf Wolkenhauer:
  Fuzzy Clustering of Short Time-Series and Unevenly Distributed Sampling Points. 330-340
  
• Elena V. Samsonova, Thomas Bäck, Margot W. Beukers, Adriaan P. IJzerman, Joost N. Kok:
  Combining and Comparing Cluster Methods in a Receptor Database. 341-351
  

Applications

• Hiroshi Mamitsuka:
  Selective Sampling with a Hierarchical Latent Variable Model. 352-363
  
• Paul O'Neill, George D. Magoulas, Xiaohui Liu:
  Obtaining Quality Microarray Data via Image Reconstruction. 364-375
  
• Heiko Hofer, Christian Borgelt, Michael R. Berthold:
  Large Scale Mining of Molecular Fragments with Wildcards. 376-385
  
• Leo Gordon, Alexey Ya. Chervonenkis, Alex J. Gammerman, Ilham A. Shahmuradov, Victor V. Solovyev:
  Genome-Wide Prokaryotic Promoter Recognition Based on Sequence Alignment Kernel. 386-396
  
• Liliana Ironi, Stefania Tentoni:
  Towards Automated Electrocardiac Map Interpretation: An Intelligent Contouring Tool Based on Spatial Aggregation. 397-408
  
• Ashwani Kumar, D. P. Agrawal, Shiv Dutt Joshi:
  Study of Canada/US Dollar Exchange Rate Movements Using Recurrent Neural Network Model of FX-Market. 409-417
  
• Christine Steinhoff, Tobias Müller, Ulrike A. Nuber, Martin Vingron:
  Gaussian Mixture Density Estimation Applied to Microarray Data. 418-429
  
• Aristoklis D. Anastasiadis, George D. Magoulas, Xiaohui Liu:
  Classification of Protein Localisation Patterns via Supervised Neural Network Learning. 430-439
  
• Steve Counsell, Xiaohui Liu, Rajaa Najjar, Stephen Swift, Allan Tucker:
  Applying Intelligent Data Analysis to Coupling Relationships in Object-Oriented Software. 440-450
  
• Martin Lauer, Martin A. Riedmiller, Thomas Ragg, Walter Baum, Michael Wigbers:
  The Smaller the Better: Comparison of Two Approaches for Sales Rate Prediction. 451-461
  

Modeling

• Clodoaldo Ap. M. Lima, André Luís Vasconcelos Coelho, Fernando J. Von Zuben:
  A Multiagent-Based Constructive Approach for Feedforward Neural Networks. 462-473
  
• Ingo Renners, Adolf Grauel:
  Evolutionary System Identification via Descriptive Takagi Sugeno Fuzzy Systems. 474-485
  
• Grace W. Rumantir, Chris S. Wallace:
  Minimum Message Length Criterion for Second-Order Polynomial Model Selection Applied to Tropical Cyclone Intensity Forecasting. 486-496
  
• Susana Vegas-Azcárate, Jorge Muruzábal:
  On the Use of the GTM Algorithm for Mode Detection. 497-508
  
• Marta Avalos, Yves Grandvalet, Christophe Ambroise:
  Regularization Methods for Additive Models. 509-520
  
• Toni M. Rath, Maximo Carreras, Paola Sebastiani:
  Automated Detection of Influenza Epidemics with Hidden Markov Models. 521-532
  
• Charles A. Sutton, Brendan Burns, Clayton T. Morrison, Paul R. Cohen:
  Guided Incremental Construction of Belief Networks. 533-543
  
• Yan Xing, Michael G. Madden, Jim Duggan, Gerard Lyons:
  Distributed Regression for Heterogeneous Data Sets. 544-553
  

(Data) Preprocessing

• Agnes Boskovitz, Rajeev Goré, Markus Hegland:
  A Logical Formalisation of the Fellegi-Holt Method of Data Cleaning. 554-565
  
• Ahlame Douzal Chouakria:
  Compression Technique Preserving Correlations of a Multivariate Temporal Sequence. 566-577
  
• François Rioult, Bruno Crémilleux:
  Condensed Representations in Presence of Missing Values. 578-588
  
• Elena Montañés, Javier Fernández, Irene Díaz, Elías F. Combarro, José Ranilla:
  Measures of Rule Quality for Feature Selection in Text Categorization. 589-598
  
• Leila Shila Shafti, Eduardo Pérez:
  Genetic Approach to Constructive Induction Based on Non-algebraic Feature Representation. 599-610
  
• Yasusi Sinohara, Teruhisa Miura:
  Active Feature Selection Based on a Very Limited Number of Entities. 611-622
  

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