Inductive Logic Programming

29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3–5, 2019, Proceedings

  • Dimitar Kazakov
  • Can Erten
Conference proceedings ILP 2019

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11770)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 11770)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Eyad Algahtani, Dimitar Kazakov
    Pages 1-15
  3. Abeer Dyoub, Stefania Costantini, Francesca A. Lisi
    Pages 26-35
  4. Francesco Giannini, Giuseppe Marra, Michelangelo Diligenti, Marco Maggini, Marco Gori
    Pages 36-45
  5. Navdeep Kaur, Gautam Kunapuli, Saket Joshi, Kristian Kersting, Sriraam Natarajan
    Pages 62-71
  6. Yin Jun Phua, Katsumi Inoue
    Pages 72-80
  7. Jonas Schouterden, Jesse Davis, Hendrik Blockeel
    Pages 98-113
  8. Stefanie Speichert, Vaishak Belle
    Pages 129-144
  9. Back Matter
    Pages 145-145

About these proceedings


This book constitutes the refereed conference proceedings of the 29th International Conference on Inductive Logic Programming, ILP 2019, held in Plovdiv, Bulgaria, in September 2019.

The 11 papers presented were carefully reviewed and selected from numerous submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data.


artificial intelligence computer programming computer systems data mining formal logic inductive logic programming (ilp) knowledge representation knowledge-based system learning logic programming machine learning semantics signal processing

Editors and affiliations

  1. 1.Department of Computer ScienceUniversity of YorkHeslingtonUK
  2. 2.Department of Computer ScienceUniversity of YorkHeslingtonUK

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