Inductive Logic Programming: 22nd International Conference, ILP 2012, Dubrovnik, Croatia, September 16-18,2012, Revised Selected papers - Tapa blanda

Sinopsis

A Relational Approach to Tool-Use Learning in Robots.- A Refinement Operator for Inducing Threaded-Variable Clauses.- Propositionalisation of Continuous Attributes beyond Simple Aggregation.- Topic Models with Relational Features for Drug Design.- Pairwise Markov Logic.- Evaluating Inference Algorithms for the Prolog Factor Language.- Polynomial Time Pattern Matching Algorithm for Ordered Graph Patterns.- Fast Parameter Learning for Markov Logic Networks Using Bayes Nets.- Bounded Least General Generalization.- Itemset-Based Variable Construction in Multi-relational Supervised Learning.- A Declarative Modeling Language for Concept Learning in Description Logics.- Identifying Driver's Cognitive Load Using Inductive Logic Programming.- Opening Doors: An Initial SRL Approach.- Probing the Space of Optimal Markov Logic Networks for Sequence Labeling.- What Kinds of Relational Features Are Useful for Statistical Learning?.- Learning Dishonesty.- Heuristic Inverse Subsumption in Full-Clausal Theories.- Learning Unordered Tree Contraction Patterns in Polynomial TimeA Relational Approach to Tool-Use Learning in Robots.- A Refinement Operator for Inducing Threaded-Variable Clauses.- Propositionalisation of Continuous Attributes beyond Simple Aggregation.- Topic Models with Relational Features for Drug Design.- Pairwise Markov Logic.- Evaluating Inference Algorithms for the Prolog Factor Language.- Polynomial Time Pattern Matching Algorithm for Ordered Graph Patterns.- Fast Parameter Learning for Markov Logic Networks Using Bayes Nets.- Bounded Least General Generalization.- Itemset-Based Variable Construction in Multi-relational Supervised Learning.- A Declarative Modeling Language for Concept Learning in Description Logics.- Identifying Driver's Cognitive Load Using Inductive Logic Programming.- Opening Doors: An Initial SRL Approach.- Probing the Space of Optimal Markov Logic Networks for Sequence Labeling.- What Kinds of Relational Features Are Useful for Statistical Learning?.-Learning Dishonesty.-Heuristic Inverse Subsumption in Full-Clausal Theories.-Learning Unordered Tree Contraction Patterns in Polynomial Time.

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