16. ILP 2006: Santiago de Compostela, Spain

Invited Papers

• Vladimir Lifschitz:
  Actions, Causation and Logic Programming. 1
  
• John McCarthy:
  Challenges to Machine Learning: Relations Between Reality and Appearance. 2-9
  
• Brian Milch, Stuart J. Russell:
  First-Order Probabilistic Languages: Into the Unknown. 10-24
  
• Bart Selman:
  Integration of Learning and Reasoning Techniques. 25
  
• Ehud Y. Shapiro:
  Injecting Life with Computers. 26
  

Special Issue Extended Abstracts

• Érick Alphonse, Aomar Osmani:
  On the Connection Between the Phase Transition of the Covering Test and the Learning Success Rate. 27-29
  
• Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen:
  Revising Probabilistic Prolog Programs. 30-33
  
• Sebastian Fröhler, Stefan Kramer:
  Inductive Logic Programming for Gene Regulation Prediction. 34-36
  
• Stephen Muggleton, Alireza Tamaddoni-Nezhad:
  QG/GA: A Stochastic Search for Progol. 37-39
  
• Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe:
  Generalized Ordering-Search for Learning Directed Probabilistic Logical Models. 40-42
  
• Fabrizio Riguzzi:
  ALLPAD: Approximate Learning of Logic Programs with Annotated Disjunctions. 43-45
  
• Ulrich Rückert, Stefan Kramer:
  Margin-Based First-Order Rule Learning. 46-48
  

Research Papers

• Érick Alphonse, Céline Rouveirol:
  Extension of the Top-Down Data-Driven Strategy to ILP. 49-63
  
• Dalal Alrajeh, Oliver Ray, Alessandra Russo, Sebastián Uchitel:
  Extracting Requirements from Scenarios with ILP. 64-78
  
• Margherita Berardi, Donato Malerba:
  Learning Recursive Patterns for Biomedical Information Extraction. 79-93
  
• Hendrik Blockeel, Wannes Meert:
  Towards Learning Non-recursive LPADs by Transforming Them into Bayesian Networks. 94-108
  
• Jianzhong Chen, Lawrence A. Kelley, Stephen Muggleton, Michael J. E. Sternberg:
  Multi-class Prediction Using Stochastic Logic Programs. 109-124
  
• Guillaume Cleuziou, Lionel Martin, Christel Vrain:
  Structuring Natural Language Data by Learning Rewriting Rules. 125-138
  
• Koichiro Doi, Tetsuya Yamashita, Akihiro Yamamoto:
  An Efficient Algorithm for Computing Kernel Function Defined with Anti-unification. 139-153
  
• Kerstin Eder, Peter A. Flach, Hsiou-Wen Hsueh:
  Towards Automating Simulation-Based Design Verification Using ILP. 154-168
  
• Vicent Estruch, César Ferri, José Hernández-Orallo, M. José Ramírez-Quintana:
  Minimal Distance-Based Generalisation Operators for First-Order Objects. 169-183
  
• Michel Ferreira, Nuno A. Fonseca, Ricardo Rocha, Tiago Soares:
  Efficient and Scalable Induction of Logic Programs Using a Deductive Database System. 184-198
  
• Barnaby Fisher, James Cussens:
  Inductive Mercury Programming. 199-213
  
• Daniel Fredouille, Christopher H. Bryant, Channa K. Jayawickreme, Steven Jupe, Simon Topp:
  An ILP Refinement Operator for Biological Grammar Learning. 214-228
  
• Rocío García-Durán, Fernando Fernández, Daniel Borrajo:
  Combining Macro-operators with Control Knowledge. 229-243
  
• Tamás Horváth, Björn Bringmann, Luc De Raedt:
  Frequent Hypergraph Mining. 244-259
  
• Tomás Horváth, Peter Vojtás:
  Induction of Fuzzy and Annotated Logic Programs. 260-274
  
• Ning Jiang, Simon Colton:
  Boosting Descriptive ILP for Predictive Learning in Bioinformatics. 275-289
  
• Andreas Karwath, Kristian Kersting:
  Relational Sequence Alignments and Logos. 290-304
  
• Francesca A. Lisi, Floriana Esposito:
  On the Missing Link Between Frequent Pattern Discovery and Concept Formation. 305-319
  
• John W. Lloyd, Kee Siong Ng:
  Learning Modal Theories. 320-334
  
• Jun-ichi Motoyama, Shinpei Urazawa, Tomofumi Nakano, Nobuhiro Inuzuka:
  A Mining Algorithm Using Property Items Extracted from Sampled Examples. 335-350
  
• Stephen Muggleton, Niels Pahlavi:
  The Complexity of Translating BLPs to RMMs. 351-365
  
• Irene M. Ong, Scott E. Topper, C. David Page Jr., Vítor Santos Costa:
  Inferring Regulatory Networks from Time Series Expression Data and Relational Data Via Inductive Logic Programming. 366-378
  
• Aline Paes, Filip Zelezný, Gerson Zaverucha, C. David Page Jr., Ashwin Srinivasan:
  ILP Through Propositionalization and Stochastic k-Term DNF Learning. 379-393
  
• Olga Skvortsova:
  theta -Subsumption Based on Object Context. 394-408
  
• Lucia Specia, Ashwin Srinivasan, Ganesh Ramakrishnan, Maria das Graças Volpe Nunes:
  Word Sense Disambiguation Using Inductive Logic Programming. 409-423
  
• Celine Vens, Jan Ramon, Hendrik Blockeel:
  ReMauve: A Relational Model Tree Learner. 424-438
  
• Monika Záková, Filip Zelezný, Javier A. García-Sedano, Cyril Masia Tissot, Nada Lavrac, Petr Kremen, Javier Molina:
  Relational Data Mining Applied to Virtual Engineering of Product Designs. 439-453
  

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