Regular Papers -- Bayesian Knowledge Corroboration with Logical Rules and User Feedback -- Learning an Affine Transformation for Non-linear Dimensionality Reduction -- NDPMine: Efficiently Mining Discriminative Numerical Features for Pattern-Based Classification -- Hidden Conditional Ordinal Random Fields for Sequence Classification -- A Unifying View of Multiple Kernel Learning -- Evolutionary Dynamics of Regret Minimization -- Recognition of Instrument Timbres in Real Polytimbral Audio Recordings -- Finding Critical Nodes for Inhibiting Diffusion of Complex Contagions in Social Networks -- Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction -- Online Knowledge-Based Support Vector Machines -- Learning with Randomized Majority Votes -- Exploration in Relational Worlds -- Efficient Confident Search in Large Review Corpora -- Learning to Tag from Open Vocabulary Labels -- A Robustness Measure of Association Rules -- Automatic Model Adaptation for Complex Structured Domains -- Collective Traffic Forecasting -- On Detecting Clustered Anomalies Using SCiForest -- Constrained Parameter Estimation for Semi-supervised Learning: The Case of the Nearest Mean Classifier -- Online Learning in Adversarial Lipschitz Environments -- Summarising Data by Clustering Items -- Classification and Novel Class Detection of Data Streams in a Dynamic Feature Space -- Latent Structure Pattern Mining -- First-Order Bayes-Ball -- Learning from Demonstration Using MDP Induced Metrics -- Demand-Driven Tag Recommendation -- Solving Structured Sparsity Regularization with Proximal Methods -- Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models -- Improved MinMax Cut Graph Clustering with Nonnegative Relaxation -- Integrating Constraint Programming and Itemset Mining -- Topic Modeling for Personalized Recommendation of Volatile Items -- Conditional Ranking on Relational Data.

This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2010, held in Barcelona, Spain, in September 2010. The 120 revised full papers presented in three volumes, together with 12 demos (out of 24 submitted demos), were carefully reviewed and selected from 658 paper submissions. In addition, 7 ML and 7 DM papers were distinguished by the program chairs on the basis of their exceptional scientific quality and high impact on the field. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. A topic widely explored from both ML and DM perspectives was graphs, with motivations ranging from molecular chemistry to social networks.