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Titlebook: Inductive Logic Programming; 6th International Wo Stephen Muggleton Conference proceedings 1997 Springer-Verlag Berlin Heidelberg 1997 indu

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Conference proceedings 1997n Stockholm, Sweden, in August 1996..The 21 full papers were carefully reviewed and selected for inclusion in the book in revised version. Also included is the invited contribution "Inductive logic programming for natural language processing" by Raymond J. Mooney. Among the topics covered are natura
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Analysis and prediction of piano performances using inductive logic programming,nductive logic programming benchmark, but also as a demonstration of the need for multiple predicate learning, sequence prediction and number handling in inductive logic programming. Furthermore, the results presented here can be considered the first original application of the clausal discovery engine Claudien.
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Noise detection and elimination applied to noise handling in a KRK chess endgame,tage that noisy examples do not influence hypothesis construction as opposed to most standard approaches to noise handling in which the learner typically tries to avoid overfitting the noisy example set. Experimental results in a KRK (king-rook-king) chess endgame domain show the potential of this novel approach to noise handling.
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Top-down induction of logic programs from incomplete samples,es. Randomly selected incomplete samples are tested with FOIL-I, QuinIan‘s FOIL and Muggleton‘s Progol. Compared with others FOIL-I can induce target relations in many cases from small incomplete samples.
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Efficient proof encoding,ts the properties of this bias to store the computed answers efficiently. We show that such encoding grows at most linearly with respect to the clause length. The result is not influenced by the presence of nondeterminism in the background knowledge.
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0302-9743 , program synthesis, proof encoding and learning in the absence of negative data, and least generalizations under implication ordering.978-3-540-63494-2978-3-540-69583-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Inductive logic programming for natural language processing,er that . acquired was more accurate than an existing hand-coded system. The paper also includes a discussion of several issues this work has raised regarding the capabilities and testing of ILP systems as well as a summary of our current research directions.
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Restructuring chain datalog programs,ssfully applied to a real-world robot navigation domain. Finally, we show that the restructuring method yields a program which can be evaluated faster than the original one. This speed up is achieved by program decompositions.
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0302-9743 96, held in Stockholm, Sweden, in August 1996..The 21 full papers were carefully reviewed and selected for inclusion in the book in revised version. Also included is the invited contribution "Inductive logic programming for natural language processing" by Raymond J. Mooney. Among the topics covered
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