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Abstract: Induction for Horn clauses from data received a major boost from the success of FOIL 1;2;3 as a pioneer clausal learning algorithm. FOIL attempts to explain a target relation (while avoiding a negative set) by incrementally adding clauses that successively increase this explained part. The residue of the target set is obtained by postulating the target set in the antecedents (body) of the generated clauses. In contrast to this, if one considers the conventional least model semantics of... (Update)
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BibTeX entry: (Update)
N. Foo and T. Tang, "An Inductive Principle for Learning Logical Definitions from Relations", Proceedings of the Seventh Australian Joint Conference on Artificial Intelligence, World Scientific Press, 1994, pp 4552. http://citeseer.ist.psu.edu/article/foo94inductive.html More
@misc{ foo94inductive,
author = "N. Foo and T. Tang",
title = "An Inductive Principle for Learning Logical Definitions from Relations",
text = "N. Foo and T. Tang, An Inductive Principle for Learning Logical Definitions
from Relations, Proceedings of the Seventh Australian Joint Conference on
Artificial Intelligence, World Scientific Press, 1994, pp 4552.",
year = "1994",
url = "citeseer.ist.psu.edu/article/foo94inductive.html" }
Citations (may not include all citations):46 Learning Logical Definitions from Relations (context) - Quinlan - 1990
12 Avoiding Pitfalls When Learning Recursive Theories (context) - Cameron-Jones, Quinlan - 1993
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