© 2015

Inductive Logic Programming

24th International Conference, ILP 2014, Nancy, France, September 14-16, 2014, Revised Selected Papers

  • Jesse Davis
  • Jan Ramon
Conference proceedings

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9046)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 9046)

Table of contents

  1. Front Matter
    Pages I-X
  2. Chowdhury Farhan Ahmed, Clément Charnay, Nicolas Lachiche, Agnès Braud
    Pages 1-15
  3. Duangtida Athakravi, Dalal Alrajeh, Krysia Broda, Alessandra Russo, Ken Satoh
    Pages 16-32
  4. Stefano Bragaglia, Oliver Ray
    Pages 33-48
  5. Clément Charnay, Nicolas Lachiche, Agnès Braud
    Pages 49-61
  6. Andrew Cropper, Stephen H. Muggleton
    Pages 62-75
  7. Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher Re, Jude Shavlik
    Pages 92-107
  8. Tony Ribeiro, Katsumi Inoue
    Pages 108-125
  9. Arti Shivram, Tushar Khot, Sriraam Natarajan, Venu Govindaraju
    Pages 126-138
  10. Dimitar Shterionov, Joris Renkens, Jonas Vlasselaer, Angelika Kimmig, Wannes Meert, Gerda Janssens
    Pages 139-153
  11. Alireza Tamaddoni-Nezhad, David Bohan, Alan Raybould, Stephen Muggleton
    Pages 154-167
  12. Dries Van Daele, Angelika Kimmig, Luc De Raedt
    Pages 168-180
  13. Celine Vens, Sofie Van Gassen, Tom Dhaene, Yvan Saeys
    Pages 181-193
  14. Pascal Welke, Tamás Horváth, Stefan Wrobel
    Pages 194-209
  15. Back Matter
    Pages 211-211

About these proceedings


This book constitutes the thoroughly refereed post-conference proceedings of the 24th International Conference on Inductive Logic Programming, ILP 2014, held in Nancy, France, in September 2014.

The 14 revised papers presented were carefully reviewed and selected from 41 submissions. The papers focus on topics such as the inducing of logic programs, learning from data represented with logic, multi-relational machine learning, learning from graphs, and applications of these techniques to important problems in fields like bioinformatics, medicine, and text mining.


Algorithms Artificial intelligence Data mining Dynamical systems Machine learning Answer set programming Attractors Boolean networks Clustering Constraints Dataset shift Meta-level constraints Probabilistic reasoning Program transformation Relational learning Robotics Statistical relational learning Stochastic optimization Structured data Supervised learning

Editors and affiliations

  • Jesse Davis
    • 1
  • Jan Ramon
    • 2
  1. 1.Department of Computer ScienceKU LeuvenLeuvenBelgium
  2. 2.Department of Computer ScienceKU LeuvenLeuvenBelgium

Bibliographic information

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