@article{Quinlan90Learning,
title = {Learning Logical Definitions from Relations},
author = {J. Ross Quinlan},
journal = {Machine Learning},
month = {August},
number = {3},
pages = {239--266},
url = {http://dx.doi.org/10.1023/A:1022699322624},
volume = {5},
year = {1990},
description = {SpringerLink - Journal Article},
abstract = {This paper describes FOIL, a system that learns Horn clauses from
data expressed as relations. FOIL is based on ideas that have proved
effective in attribute-value learning systems, but extends them to
a first-order formalism. This new system has been applied successfully
to several tasks taken from the machine learning literature. ER -},
timestamp = {2007.12.19}, owner = {martin},
keywords = {FOIL ILP Induction empirical_learning first_order_rules inductive_logic_programming inductive_programming relational_data }
}
::