Knowledge Discovery in Databases: PKDD 2007

This book constitutes the refereed proceedings of the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2007, held in Warsaw, Poland, co-located with ECML 2007, the 18th European Conference on Machine Learning. The 28 revised full papers and 35 revised short papers present original results on leading-edge subjects of knowledge discovery from conventional and complex data and address all current issues in the area.

Inhalt

Invited Talks.- Learning, Information Extraction and the Web.- Putting Things in Order: On the Fundamental Role of Ranking in Classification and Probability Estimation.- Mining Queries.- Adventures in Personalized Information Access.- Long Papers.- Experiment Databases: Towards an Improved Experimental Methodology in Machine Learning.- Using the Web to Reduce Data Sparseness in Pattern-Based Information Extraction.- A Graphical Model for Content Based Image Suggestion and Feature Selection.- Efficient AUC Optimization for Classification.- Finding Transport Proteins in a General Protein Database.- Classification of Web Documents Using a Graph-Based Model and Structural Patterns.- Context-Specific Independence Mixture Modelling for Protein Families.- An Algorithm to Find Overlapping Community Structure in Networks.- Privacy Preserving Market Basket Data Analysis.- Feature Extraction from Sensor Data Streams for Real-Time Human Behaviour Recognition.- Generating Social Network Features for Link-Based Classification.- An Empirical Comparison of Exact Nearest Neighbour Algorithms.- Site-Independent Template-Block Detection.- Statistical Model for Rough Set Approach to Multicriteria Classification.- Classification of Anti-learnable Biological and Synthetic Data.- Improved Algorithms for Univariate Discretization of Continuous Features.- Efficient Weight Learning for Markov Logic Networks.- Classification in Very High Dimensional Problems with Handfuls of Examples.- Domain Adaptation of Conditional Probability Models Via Feature Subsetting.- Learning to Detect Adverse Traffic Events from Noisily Labeled Data.- IKNN: Informative K-Nearest Neighbor Pattern Classification.- Finding Outlying Items in Sets of Partial Rankings.- Speeding Up Feature Subset Selection Through Mutual Information Relevance Filtering.- A Comparison of Two Approaches to Classify with Guaranteed Performance.- Towards Data Mining Without Information on Knowledge Structure.- Relaxation Labeling for Selecting and Exploiting Efficiently Non-local Dependencies in Sequence Labeling.- Bridged Refinement for Transfer Learning.- A Prediction-Based Visual Approach for Cluster Exploration and Cluster Validation by HOV3.- Short Papers.- Flexible Grid-Based Clustering.- Polyp Detection in Endoscopic Video Using SVMs.- A Density-Biased Sampling Technique to Improve Cluster Representativeness.- Expectation Propagation for Rating Players in Sports Competitions.- Efficient Closed Pattern Mining in Strongly Accessible Set Systems (Extended Abstract).- Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach.- Realistic Synthetic Data for Testing Association Rule Mining Algorithms for Market Basket Databases.- Learning Multi-dimensional Functions: Gas Turbine Engine Modeling.- Constructing High Dimensional Feature Space for Time Series Classification.- A Dynamic Clustering Algorithm for Mobile Objects.- A Method for Multi-relational Classification Using Single and Multi-feature Aggregation Functions.- MINI: Mining Informative Non-redundant Itemsets.- Stream-Based Electricity Load Forecast.- Automatic Hidden Web Database Classification.- Pruning Relations for Substructure Discovery of Multi-relational Databases.- The Most Reliable Subgraph Problem.- Matching Partitions over Time to Reliably Capture Local Clusters in Noisy Domains.- Searching for Better Randomized Response Schemes for Privacy-Preserving Data Mining.- Pre-processing Large Spatial Data Sets with Bayesian Methods.- Tag Recommendations in Folksonomies.- Providing Naïve Bayesian Classifier-Based Private Recommendations on Partitioned Data.- Multi-party, Privacy-Preserving Distributed Data Mining Using a Game Theoretic Framework.- Multilevel Conditional Fuzzy C-Means Clustering of XML Documents.- Uncovering Fraud in Direct Marketing Data with a Fraud Auditing Case Builder.- Real Time GPU-Based Fuzzy ART Skin Recognition.- A Cooperative Game Theoretic Approach to Prototype Selection.- Dynamic Bayesian Networks for Real-Time Classification of Seismic Signals.- Robust Visual Mining of Data with Error Information.- An Effective Approach to Enhance Centroid Classifier for Text Categorization.- Automatic Categorization of Human-Coded and Evolved CoreWar Warriors.- Utility-Based Regression.- Multi-label Lazy Associative Classification.- Visual Exploration of Genomic Data.- Association Mining in Large Databases: A Re-examination of Its Measures.- Semantic Text Classification of Emergent Disease Reports.