Inductive Logic Programming: 30th International Conference, ILP 2021, Virtual Event, October 25–27, 2021, Proceedings

Inductive Logic Programming: 30th International Conference, ILP 2021, Virtual Event, October 25–27, 2021, Proceedings

Author
Nikos Katzouris, Alexander Artikis
Publisher
Springer
Language
English
Year
2022
Page
292
ISBN
3030974537,9783030974534
File Type
pdf
File Size
13.5 MiB

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.

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