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.
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.
Overview
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.