Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers

Vladimir Lifschitz (auth.), Stephen Muggleton, Ramon Otero, Alireza Tamaddoni-Nezhad (eds.)3540738460, 9783540738466

The inherent dangers of change are often summed up in the misquoted Chinese curse “May you live in interesting times.” The submission procedure for the 16th International Conference of Inductive Logic Programming (ILP 2006) was a radical (hopefully interesting but not cursed) departure from previous years. Submissions were requested in two phases. The ?rst phase involved submission of short papers (three pages) which were then presented at the conference and included in a short papers proceedings. In the second phase, reviewers selected papersforlongpapersubmission(15pagesmaximum).Thesewerethenassessed by the same reviewers, who then decided which papers to include in the journal special issue and proceedings. In the ?rst phase there were a record 77 papers, comparedto the usual20 orso long papersofpreviousyears.Eachpaper was- viewed by three reviewers. Out of these, 71 contributors were invited to submit long papers. Out of the long paper submissions, 7 were selected for the – chine Learning Journal special issue and 27 were accepted for the proceedings. In addition, two papers were nominated by Program Committee referees for the applications prize and two for the theory prize. The papers represent the div- sity and vitality in present ILP research including ILP theory, implementations, search and phase transition, distributed and large-scale learning, probabilistic ILP, biological applications, natural language learning and planning and action learning.

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Table of contents :
Front Matter….Pages –
Actions, Causation and Logic Programming….Pages 1-1
Challenges to Machine Learning: Relations Between Reality and Appearance….Pages 2-9
First-Order Probabilistic Languages: Into the Unknown….Pages 10-24
Integration of Learning and Reasoning Techniques….Pages 25-25
Injecting Life with Computers….Pages 26-26
On the Connection Between the Phase Transition of the Covering Test and the Learning Success Rate….Pages 27-29
Revising Probabilistic Prolog Programs….Pages 30-33
Inductive Logic Programming for Gene Regulation Prediction….Pages 34-36
QG/GA: A Stochastic Search for Progol….Pages 37-39
Generalized Ordering-Search for Learning Directed Probabilistic Logical Models….Pages 40-42
ALLPAD: Approximate Learning of Logic Programs with Annotated Disjunctions….Pages 43-45
Margin-Based First-Order Rule Learning….Pages 46-48
Extension of the Top-Down Data-Driven Strategy to ILP….Pages 49-63
Extracting Requirements from Scenarios with ILP….Pages 64-78
Learning Recursive Patterns for Biomedical Information Extraction….Pages 79-93
Towards Learning Non-recursive LPADs by Transforming Them into Bayesian Networks….Pages 94-108
Multi-class Prediction Using Stochastic Logic Programs….Pages 109-124
Structuring Natural Language Data by Learning Rewriting Rules….Pages 125-138
An Efficient Algorithm for Computing Kernel Function Defined with Anti-unification….Pages 139-153
Towards Automating Simulation-Based Design Verification Using ILP….Pages 154-168
Minimal Distance-Based Generalisation Operators for First-Order Objects….Pages 169-183
Efficient and Scalable Induction of Logic Programs Using a Deductive Database System….Pages 184-198
Inductive Mercury Programming….Pages 199-213
An ILP Refinement Operator for Biological Grammar Learning….Pages 214-228
Combining Macro-operators with Control Knowledge….Pages 229-243
Frequent Hypergraph Mining….Pages 244-259
Induction of Fuzzy and Annotated Logic Programs….Pages 260-274
Boosting Descriptive ILP for Predictive Learning in Bioinformatics….Pages 275-289
Relational Sequence Alignments and Logos….Pages 290-304
On the Missing Link Between Frequent Pattern Discovery and Concept Formation….Pages 305-319
Learning Modal Theories….Pages 320-334
A Mining Algorithm Using Property Items Extracted from Sampled Examples….Pages 335-350
The Complexity of Translating BLPs to RMMs….Pages 351-365
Inferring Regulatory Networks from Time Series Expression Data and Relational Data Via Inductive Logic Programming….Pages 366-378
ILP Through Propositionalization and Stochastic k-Term DNF Learning….Pages 379-393
θ -Subsumption Based on Object Context….Pages 394-408
Word Sense Disambiguation Using Inductive Logic Programming….Pages 409-423
ReMauve: A Relational Model Tree Learner….Pages 424-438
Relational Data Mining Applied to Virtual Engineering of Product Designs….Pages 439-453
Back Matter….Pages –