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 Theory and Practice of Risk Assessment by
Cover of the book Risk Analysis of Natural Hazards by
Cover of the book Multi-Criteria Decision Making in Maritime Studies and Logistics by
Cover of the book Edge-to-Edge Mitral Repair by
Cover of the book Zika Virus Infection by
Cover of the book Towards Integrating Control and Information Theories by
Cover of the book From Bilateral Arbitral Tribunals and Investment Courts to a Multilateral Investment Court by
Cover of the book Direct Licensing and the Music Industry by
Cover of the book Heterogeneous Data Management, Polystores, and Analytics for Healthcare by
Cover of the book New Developments in Competition Law and Economics by
Cover of the book Evolutionary Algorithms and Neural Networks by
Cover of the book Researching Newsreels by
Cover of the book Electrochemistry in a Divided World by
Cover of the book Grand Timely Topics in Software Engineering by
Cover of the book Information Security Theory and Practice 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