In 2006, the 6th collocated ECML/PKDD took place during September 18-22, when the Humboldt-Universität zu Berlin hosted the 17th European Conference on Machine Learning (ECML) and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD).

Invited Talks.- On Temporal Evolution in Data Streams.- The Future of CiteSeer: CiteSeerx.- Learning to Have Fun.- Winning the DARPA Grand Challenge.- Challenges of Urban Sensing.- Long Papers.- SD-Map – A Fast Algorithm for Exhaustive Subgroup Discovery.- Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics.- Clustering Scientific Literature Using Sparse Citation Graph Analysis.- VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequences.- Don’t Be Afraid of Simpler Patterns.- An Adaptive Prequential Learning Framework for Bayesian Network Classifiers.- Adaptive Active Classification of Cell Assay Images.- Learning Parameters in Entity Relationship Graphs from Ranking Preferences.- Detecting Fraudulent Personalities in Networks of Online Auctioneers.- Measuring Constraint-Set Utility for Partitional Clustering Algorithms.- Discovery of Interesting Regions in Spatial Data Sets Using Supervised Clustering.- Optimal String Mining Under Frequency Constraints.- k-Anonymous Decision Tree Induction.- Closed Sets for Labeled Data.- Finding Trees from Unordered 0–1 Data.- Web Communities Identification from Random Walks.- Information Marginalization on Subgraphs.- Why Does Subsequence Time-Series Clustering Produce Sine Waves?.- Transductive Learning for Text Classification Using Explicit Knowledge Models.- Exploring Multiple Communities with Kernel-Based Link Analysis.- Distribution Rules with Numeric Attributes of Interest.- Tractable Models for Information Diffusion in Social Networks.- Efficient Spatial Classification Using Decoupled Conditional Random Fields.- Group SAX: Extending the Notion of Contrast Sets to Time Series and Multimedia Data.- An Attacker’s View of Distance Preserving Maps for Privacy Preserving Data Mining.- A Scalable Distributed Stream Mining System for Highway Traffic Data.- K-Landmarks: Distributed Dimensionality Reduction for Clustering Quality Maintenance.- The Discrete Basis Problem.- Evaluation of Summarization Schemes for Learning in Streams.- Efficient Mining of Correlation Patterns in Spatial Point Data.- Improving Functional Modularity in Protein-Protein Interactions Graphs Using Hub-Induced Subgraphs.- Refining Aggregate Conditions in Relational Learning.- Measuring to Fit: Virtual Tailoring Through Cluster Analysis and Classification.- RIVA: Indexing and Visualization of High-Dimensional Data Via Dimension Reorderings.- Distributed Subgroup Mining.- Network Flow for Collaborative Ranking.- Short Papers.- Finding Hierarchies of Subspace Clusters.- Integrating Pattern Mining in Relational Databases.- Discovering Patterns in Real-Valued Time Series.- Classification of Dementia Types from Cognitive Profiles Data.- When Efficient Model Averaging Out-Performs Boosting and Bagging.- Peak-Jumping Frequent Itemset Mining Algorithms.- Autonomous Visualization.- Naive Bayes for Text Classification with Unbalanced Classes.- Knowledge-Conscious Data Clustering.- On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining.- Frequent Pattern Discovery Without Binarization: Mining Attribute Profiles.- Efficient Name Disambiguation for Large-Scale Databases.- Adaptive Segmentation-Based Symbolic Representations of Time Series for Better Modeling and Lower Bounding Distance Measures.- A Feature Generation Algorithm for Sequences with Application to Splice-Site Prediction.- Discovering Image-Text Associations for Cross-Media Web Information Fusion.- Mining Sequences of Temporal Intervals.- Pattern Teams.- Compression Picks Item Sets That Matter.- Discovering Overlapping Communities of Named Entities.- Closed Non-derivable Itemsets.- Learning a Distance Metric for Object Identification Without Human Supervision.- Towards Association Rules with Hidden Variables.- A Data Mining Approach to the Joint Evaluation of Field and Manufacturing Data in Automotive Industry.- Incremental Aspect Models for Mining Document Streams.- Learning Approximate MRFs from Large Transaction Data.- Similarity Search for Multi-dimensional NMR-Spectra of Natural Products.