Inductive Logic Programming

27th International Conference, ILP 2017, Orléans, France, September 4-6, 2017, Revised Selected Papers

Nonfiction, Science & Nature, Mathematics, Logic, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Inductive Logic Programming by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319780900
Publisher: Springer International Publishing Publication: March 19, 2018
Imprint: Springer Language: English
Author:
ISBN: 9783319780900
Publisher: Springer International Publishing
Publication: March 19, 2018
Imprint: Springer
Language: English

This book constitutes the thoroughly refereed post-conference proceedings of the 27th International Conference on Inductive Logic Programming, ILP 2017, held in Orléans, France, in September 2017.
The 12 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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book constitutes the thoroughly refereed post-conference proceedings of the 27th International Conference on Inductive Logic Programming, ILP 2017, held in Orléans, France, in September 2017.
The 12 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 books from Springer International Publishing

Cover of the book Finite Time Thermodynamics of Power and Refrigeration Cycles by
Cover of the book Spatial Visualization and Professional Competence by
Cover of the book Perspectives on the Archaeology of Pipes, Tobacco and other Smoke Plants in the Ancient Americas by
Cover of the book Current and Emerging mHealth Technologies by
Cover of the book Advances in Service-Oriented and Cloud Computing by
Cover of the book Simulation and Synthesis in Medical Imaging by
Cover of the book Radiation Hardened CMOS Integrated Circuits for Time-Based Signal Processing by
Cover of the book Distributed Computing and Monitoring Technologies for Older Patients by
Cover of the book Weak-Coupling Theory of Topological Superconductivity by
Cover of the book Cellular Injury in Liver Diseases by
Cover of the book Open Problems in Spectral Dimensionality Reduction by
Cover of the book Disaster Robotics by
Cover of the book EPFL Lectures on Conformal Field Theory in D ≥ 3 Dimensions by
Cover of the book Disaster Forensics by
Cover of the book Intelligent Robotics and Applications by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy