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Abstract: Many ILP systems, such as GOLEM, FOIL, and MIS, take advantage of user supplied meta-knowledge to restrict the hypothesis space. This meta-knowledge can be in the form of type information about arguments in the predicate being learned, or it can be information about whether a certain argument in the predicate is functionally dependent on the other arguments (supplied as mode information). This meta knowledge is explicitly supplied to an ILP system in addition to the data. The present paper... (Update)
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...Current personnel are Claude Sammut, Arun Sharma, John Shepherd, Eric McCreath and Michael Bain. For sample publications, refer to [3, 4, 15, 26] and for further information, consult http: www.cse.unsw.edu.au . see also Knowledge Systems Group. ffl University of...
...simply from the syntax. Other types are induced from the example and the background knowledge. This process is thoroughly examined in [13]. Also, since the search space is restricted to determinate clauses, it is useful to know the mode restrictions for each predicate prior...
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BibTeX entry: (Update)
E. McCreath and A. Sharma. Extraction of meta-knowledge to restrict the hypothesis space for ILP systems. In X. Yao, editor, Proceedings of the Eighth Australian Joint Conference on Artificial Intelligence, pages 75--82. World Scientific, November 1995. http://citeseer.ist.psu.edu/mccreath95extraction.html More
@misc{ mccreath95extraction,
author = "E. McCreath and A. Sharma",
title = "Extraction of meta-knowledge to restrict the hypothesis space for ILP systems",
text = "E. McCreath and A. Sharma. Extraction of meta-knowledge to restrict the
hypothesis space for ILP systems. In X. Yao, editor, Proceedings of the
Eighth Australian Joint Conference on Artificial Intelligence, pages 75--82.
World Scientific, November 1995.",
year = "1995",
url = "citeseer.ist.psu.edu/mccreath95extraction.html" }
Citations (may not include all citations):271 Efficient induction of logic programs - Muggleton, Feng - 1990
212 Inductive Logic Programming: Techniques and Applications (context) - Lavrac, Dzeroski - 1994
130 Inverse entailment and progol - Muggleton - 1995
127 Prolog Programming for Artificial Intelligence (context) - Bratko - 1990
68 Controlling the complexity of learning in logic through synt.. - Kietz, Wrobel - 1991
63 Inductive inference of theories from facts (context) - Shapiro - 1981
57 Handling noise in inductive logic programming (context) - Dzeroski - 1991
39 An interactive system to learn functional logic programs (context) - Bergadano, Gunetti - 1994
31 Efficient top-down induction of logic programs (context) - Cameron-Jones, Quinlan - 1994
11 Induction of prolog programs with markus (context) - Grobelnik - 1994
11 Background knowledge and declarative bias in inductive conce.. (context) - Lavrac, Dzeroski - 1992
6 Refinement strategies for inductive learning of simple prolo.. (context) - Kirschenbaum, Sterling - 1991
4 Balanced cooperative modelling (context) - Morik - 1991
1 The problem of induction and machine learning (context) - Bergadano - 1991
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