Inductive Logic Programming
28th International Conference, ILP 2018, Ferrara, Italy, September 2-4, 2018, Proceedings
Published on 24. August 2018
Book
Paperback/Softback
IX, 173 pages
978-3-319-99959-3 (ISBN)
Description
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.
More details
Series
Edition
2018 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
20 farbige Abbildungen, 181 s/w Abbildungen
IX, 173 p. 201 illus., 20 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 11 mm
Weight
295 gr
ISBN-13
978-3-319-99959-3 (9783319999593)
DOI
10.1007/978-3-319-99960-9
Schweitzer Classification
Other editions
Additional editions
Fabrizio Riguzzi | Elena Bellodi | Riccardo Zese
Inductive Logic Programming
28th International Conference, ILP 2018, Ferrara, Italy, September 2-4, 2018, Proceedings
E-Book
08/2018
Springer
€53.49
Available for download
Content
Derivation reduction of metarules in meta-interpretive learning.- Large-Scale Assessment of Deep Relational Machines.- How much can experimental cost be reduced in active learning of agent strategies?.- Diagnostics of Trains with Semantic Diagnostics Rules.- The game of Bridge: a challenge for ILP.- Sampling-Based SAT/ASP Multi-Model Optimization as a Framework for Probabilistic Inference.- Explaining Black-box Classifiers with ILP - Empowering LIME with Aleph to Approximate Non-linear Decisions with Relational Rules.- Learning Dynamics with Synchronous, Asynchronous and General Semantics.- Was the Year 2000 a Leap Year? Step-wise Narrowing Theories with Metagol.- Targeted End-to-end Knowledge Graph Decomposition.