Inductive logic programming : 20th international conference, ILP 2010, Florence, Italy, June 27-30, 2010 : revised papers / Paolo Frasconi, Francesca A. Lisi (eds.).

Includes bibliographical references and index.

This book constitutes the thoroughly refereed post-proceedings of the 20th International Conference on Inductive Logic Programming, ILP 2010, held in Florence, Italy in June 2010. The 11 revised full papers and 15 revised short papers presented together with abstracts of three invited talks were carefully reviewed and selected during two rounds of refereeing and revision. All current issues in inductive logic programming, i.e. in logic programming for machine learning are addressed, in particular statistical learning and other probabilistic approaches to machine learning are reflected.

Machine generated contents note: Abstracts of Invited Talks -- Rule Interchange Format: Logic Programming's Second Wind? / Michael Kifer -- Practical Probabilistic Programming / Avi Pfeffer -- Probabilistic Relational Learning and Inductive Logic Programming at a Global Scale / David Poole -- Research Papers -- Learning Multi-class Theories in ILP / Peter A. Flach -- Numerical Refinement Operator Based on Multi-Instance Learning / Stefan Kramer -- Not Far Away from Home: A Relational Distance-Based Approach to Understanding Images of Houses / Luc De Raedt -- Approximate Inference for Logic Programs with Annotated Disjunctions / Fabrizio Riguzzi -- Approximate Bayesian Computation for the Parameters of PRISM Programs / James Cussens -- Probabilistic Rule Learning / Ingo Thon -- Interactive Discriminative Mining of Chemical Fragments / Rui Camacho -- MMRF for Proteome Annotation Applied to Human Protein Disease Prediction / Araceli Sanchis -- Extending ProbLog with Continuous Distributions / Luc De Raedt -- Multivariate Prediction for Learning on the Semantic Web / Hans-Peter Kriegel -- Learning Action Descriptions of Opponent Behaviour in the Robocup 2D Simulation Environment / Jose Santos -- Hypothesizing about Causal Networks with Positive and Negative Effects by Meta-level Abduction / Hidetomo Nabeshima -- BET: An Inductive Logic Programming Workbench / Ashwin Srinivasan -- Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples / Filip Zelezny -- Learning Discriminant Rules as a Minimal Saturation Search / Christel Vrain -- Variation of Background Knowledge in an Industrial Application of ILP / Michael J.E. Sternberg -- Pruning Search Space for Weighted First Order Horn Clause Satisfiability / Ganesh Ramakrishnan -- ^ Multi-relational Pattern Mining Based-on Combination of Properties with Preserving Their Structure in Examples / Nobuhiro Inuzuka

Note continued: Learning from Noisy Data Using a Non-covering ILP Algorithm / Ivan Bratko -- Can HOLL Outperform FOLL? / Stephen Muggleton -- Incremental Learning of Relational Action Models in Noisy Environments / Celine Rouveirol -- When Does It Pay Off to Use Sophisticated Entailment Engines in ILP? / Stephen Muggleton -- Stochastic Refinement / Stephen Muggleton -- Fire! Firing Inductive Rules from Economic Geography for Fire Risk Detection / Michel Ferreira -- Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge / Jude Shavlik -- Speeding Up Planning through Minimal Generalizations of Partially Ordered Plans / Filip Zelezny.