Inductive Logic Programming

25th International Conference, ILP 2015, Kyoto, Japan, August 20-22, 2015, Revised Selected Papers

  • Katsumi Inoue
  • Hayato Ohwada
  • Akihiro Yamamoto
Conference proceedings ILP 2015

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9575)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 9575)

Table of contents

  1. Front Matter
    Pages I-X
  2. Laura Antanas, Plinio Moreno, Luc De Raedt
    Pages 1-14
  3. Clément Charnay, Nicolas Lachiche, Agnès Braud
    Pages 15-29
  4. Giuseppe Cota, Riccardo Zese, Elena Bellodi, Fabrizio Riguzzi, Evelina Lamma
    Pages 30-45
  5. Andrew Cropper, Alireza Tamaddoni-Nezhad, Stephen H. Muggleton
    Pages 46-59
  6. Golnoosh Farnadi, Stephen H. Bach, Marjon Blondeel, Marie-Francine Moens, Lise Getoor, Martine De Cock
    Pages 60-75
  7. Ondřej Kuželka, Jesse Davis, Steven Schockaert
    Pages 91-105
  8. Ondřej Kuželka, Jan Ramon
    Pages 106-121
  9. Carlos Alberto Martínez-Angeles, Inês Dutra, Vítor Santos Costa, Jorge Buenabad-Chávez
    Pages 122-136
  10. Samuel R. Neaves, Louise A. C. Millard, Sophia Tsoka
    Pages 137-151
  11. Francesco Orsini, Paolo Frasconi, Luc De Raedt
    Pages 152-165
  12. Sergey Paramonov, Matthijs van Leeuwen, Marc Denecker, Luc De Raedt
    Pages 166-182
  13. Chiaki Sakama, Tony Ribeiro, Katsumi Inoue
    Pages 183-199
  14. Ashwin Srinivasan, Michael Bain, Deepika Vatsa, Sumeet Agarwal
    Pages 200-214
  15. Back Matter
    Pages 215-215

About these proceedings


This book constitutes the thoroughly refereed post-conference proceedings of the 25th International Conference on Inductive Logic Programming, ILP 2015, held in Kyoto, Japan, in August 2015.

The 14 revised papers presented were carefully reviewed and selected from 44 submissions. The papers focus on topics such as theories, algorithms, representations and languages, systems and applications of ILP, and cover all areas of learning in logic, relational learning, relational data mining, statistical relational learning, multi-relational data mining, relational reinforcement learning, graph mining, connections with other learning paradigms, among others.


algorithms artificial intelligence data mining formal methods knowledge based systems knowledge representation logic programming machine learning ontology relational learning statistical relational learning

Editors and affiliations

  • Katsumi Inoue
    • 1
  • Hayato Ohwada
    • 2
  • Akihiro Yamamoto
    • 3
  1. 1.National Institute of InformaticsTokyoJapan
  2. 2.Tokyo University of ScienceNodaJapan
  3. 3.Kyoto UniversityKyotoJapan

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-319-40565-0
  • Online ISBN 978-3-319-40566-7
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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