Inductive Logic Programming

1. Front Matter

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2. Abstracts of Invited Talks

   1. Rule Interchange Format: Logic Programming’s Second Wind?

      • Michael Kifer

      Pages 1-1

   2. Practical Probabilistic Programming

      • Avi Pfeffer

      Pages 2-3

   3. Probabilistic Relational Learning and Inductive Logic Programming at a Global Scale

      • David Poole

      Pages 4-5

3. Research Papers

   1. Learning Multi-class Theories in ILP

      • Tarek Abudawood, Peter A. Flach

      Pages 6-13

   2. A Numerical Refinement Operator Based on Multi-Instance Learning

      • Erick Alphonse, Tobias Girschick, Fabian Buchwald, Stefan Kramer

      Pages 14-21

   3. Not Far Away from Home: A Relational Distance-Based Approach to Understanding Images of Houses

      • Laura Antanas, Martijn van Otterlo, José Oramas M., Tinne Tuytelaars, Luc De Raedt

      Pages 22-29

   4. Approximate Inference for Logic Programs with Annotated Disjunctions

      • Stefano Bragaglia, Fabrizio Riguzzi

      Pages 30-37

   5. Approximate Bayesian Computation for the Parameters of PRISM Programs

      • James Cussens

      Pages 38-46

   6. Probabilistic Rule Learning

      • Luc De Raedt, Ingo Thon

      Pages 47-58

   7. Interactive Discriminative Mining of Chemical Fragments

      • Nuno A. Fonseca, Max Pereira, Vítor Santos Costa, Rui Camacho

      Pages 59-66

   8. MMRF for Proteome Annotation Applied to Human Protein Disease Prediction

      • Beatriz García-Jiménez, Agapito Ledezma, Araceli Sanchis

      Pages 67-75

   9. Extending ProbLog with Continuous Distributions

      • Bernd Gutmann, Manfred Jaeger, Luc De Raedt

      Pages 76-91

   10. Multivariate Prediction for Learning on the Semantic Web

       • Yi Huang, Volker Tresp, Markus Bundschus, Achim Rettinger, Hans-Peter Kriegel

       Pages 92-104

   11. Learning Action Descriptions of Opponent Behaviour in the Robocup 2D Simulation Environment

       • Alberto Illobre, Jorge Gonzalez, Ramon Otero, Jose Santos

       Pages 105-113

   12. Hypothesizing about Causal Networks with Positive and Negative Effects by Meta-level Abduction

       • Katsumi Inoue, Andrei Doncescu, Hidetomo Nabeshima

       Pages 114-129

   13. BET : An Inductive Logic Programming Workbench

       • Srihari Kalgi, Chirag Gosar, Prasad Gawde, Ganesh Ramakrishnan, Kekin Gada, Chander Iyer et al.

       Pages 130-137

   14. Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples

       • Ondřej Kuželka, Filip Železný

       Pages 138-145

   15. Learning Discriminant Rules as a Minimal Saturation Search

       • Matthieu Lopez, Lionel Martin, Christel Vrain

       Pages 146-157

   16. Variation of Background Knowledge in an Industrial Application of ILP

       • Stephen H. Muggleton, Jianzhong Chen, Hiroaki Watanabe, Stuart J. Dunbar, Charles Baxter, Richard Currie et al.

       Pages 158-170

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.

• algorithmic learning
• approximate inference
• computational learning
• data mining
• probabilistic programming
• relational learning
• rule learning

• Dipartimento di Sistemi e Informatica, Universitá degli Studi di Firenze, Italy

  Paolo Frasconi

• Dipartimento di Informatica, Università degli Studi di Bari, Bari, Italy

  Francesca A. Lisi

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