Inductive Logic Programming

30th International Conference, ILP 2021, Virtual Event, October 25–27, 2021, Proceedings

• Author(s): Nikos Katzouris, Alexander Artikis,
• Publisher: Springer Nature
• Pages: 283
• ISBN_10: 3030974545
  ISBN_13: 9783030974541
  
• Language: en
• Categories: Computers / Artificial Intelligence / General , Computers / Online Services , Computers / Languages / General , Computers / Programming / General , Mathematics / Logic , Computers / Information Technology , Computers / Internet / General , Computers / Networking / General , Mathematics / Discrete Mathematics ,

Description:... This book constitutes the refereed conference proceedings of the 30th International Conference on Inductive Logic Programming, ILP 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually.

The 16 papers and 3 short papers presented were carefully reviewed and selected from 19 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.