Journal of Artificial Intelligence Research 16 (2002), pp. 135-166. Submitted 7/01; published 2/02.
© 2002 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.
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Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs

Hendrik Blockeel$^1$ - Luc Dehaspe$^2$ - Bart Demoen$^1$ - Gerda Janssens$^1$ - Jan Ramon$^1$ - Henk Vandecasteele$^2$ -
$^1$ Katholieke Universiteit Leuven, Department of Computer Science
Celestijnenlaan 200A, B-3001 Leuven, Belgium
$^2$ PharmaDM, Ambachtenlaan 54D, B-3001 Leuven, Belgium

Abstract:

Inductive logic programming, or relational learning, is a powerful paradigm for machine learning or data mining. However, in order for ILP to become practically useful, the efficiency of ILP systems must improve substantially. To this end, the notion of a query pack is introduced: it structures sets of similar queries. Furthermore, a mechanism is described for executing such query packs. A complexity analysis shows that considerable efficiency improvements can be achieved through the use of this query pack execution mechanism. This claim is supported by empirical results obtained by incorporating support for query pack execution in two existing learning systems.