Inductive Logic Programming (eBook, PDF)

17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers
Redaktion: Blockeel, Hendrik; Tadepalli, Prasad; Shavlik, Jude; Ramon, Jan

• Format: PDF

Produktbeschreibung

This book contains the post-conference proceedings of the 17th International Conference on Inductive Logic Programming. It covers current topics in inductive logic programming, from theoretical and methodological issues to advanced applications.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 307
• Erscheinungstermin: 23. Februar 2008
• Englisch
• ISBN-13: 9783540784692
• Artikelnr.: 44132066

Inhaltsangabe

Invited Talks.- Learning with Kernels and Logical Representations.- Beyond Prediction: Directions for Probabilistic and Relational Learning.- Extended Abstracts.- Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract).- Learning Directed Probabilistic Logical Models Using Ordering-Search.- Learning to Assign Degrees of Belief in Relational Domains.- Bias/Variance Analysis for Relational Domains.- Full Papers.- Induction of Optimal Semantic Semi-distances for Clausal Knowledge Bases.- Clustering Relational Data Based on Randomized Propositionalization.- Structural Statistical Software Testing with Active Learning in a Graph.- Learning Declarative Bias.- ILP :- Just Trie It.- Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning.- Empirical Comparison of "Hard" and "Soft" Label Propagation for Relational Classification.- A Phase Transition-Based Perspective on Multiple Instance Kernels.- Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates.- Applying Inductive Logic Programming to Process Mining.- A Refinement Operator Based Learning Algorithm for the Description Logic.- Foundations of Refinement Operators for Description Logics.- A Relational Hierarchical Model for Decision-Theoretic Assistance.- Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming.- Revising First-Order Logic Theories from Examples Through Stochastic Local Search.- Using ILP to Construct Features for Information Extraction from Semi-structured Text.- Mode-Directed Inverse Entailment for Full Clausal Theories.- Mining of Frequent Block Preserving Outerplanar Graph Structured Patterns.- Relational Macros for Transfer in Reinforcement Learning.- Seeing theForest Through the Trees.- Building Relational World Models for Reinforcement Learning.- An Inductive Learning System for XML Documents.