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Inductive Logic Programming

28th International Conference, ILP 2018, Ferrara, Italy, September 2–4, 2018, Proceedings

  • Fabrizio Riguzzi
  • Elena Bellodi
  • Riccardo Zese
Conference proceedings ILP 2018

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11105)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 11105)

Table of contents

  1. Front Matter
    Pages I-IX
  2. Andrew Cropper, Sophie Tourret
    Pages 1-21
  3. Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Oghenejokpeme I. Orhobor, Ross D. King
    Pages 22-37
  4. Evgeny Kharlamov, Ognjen Savković, Martin Ringsquandl, Guohui Xiao, Gulnar Mehdi, Elem Güzel Kalayc et al.
    Pages 54-71
  5. Swann Legras, Céline Rouveirol, Véronique Ventos
    Pages 72-87
  6. Tony Ribeiro, Maxime Folschette, Morgan Magnin, Olivier Roux, Katsumi Inoue
    Pages 118-140
  7. Blaž Škrlj, Jan Kralj, Nada Lavrač
    Pages 157-171
  8. Back Matter
    Pages 173-173

About these proceedings

Introduction

This book constitutes the refereed conference proceedings of the 28th International Conference on Inductive Logic Programming, ILP 2018, held in Ferrara, Italy, in September 2018.

The 10 full 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.

Keywords

artificial intelligence computer programming domain knowledge evolutionary algorithms inductive logic programming learning algorithms logic programming logic programs ontologies probabilistic graphical models problem solving programming languages relational data mining relational learning semantics supervised learning

Editors and affiliations

  1. 1.University of FerraraFerraraItaly
  2. 2.University of FerraraFerraraItaly
  3. 3.University of FerraraFerraraItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-99960-9
  • Copyright Information Springer Nature Switzerland AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-99959-3
  • Online ISBN 978-3-319-99960-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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