Journal of Artificial Intelligence Research
pp. 135-166. Submitted 7/01; published 2/02.
© 2002 AI Access Foundation
and Morgan Kaufmann Publishers.
All rights reserved.
Postscript and PDF versions of this document are
Improving the Efficiency of Inductive Logic Programming Through the
Use of Query Packs
Hendrik Blockeel - Luc Dehaspe - Bart Demoen -
Gerda Janssens - Jan Ramon - Henk Vandecasteele -
Katholieke Universiteit Leuven, Department of Computer Science
Celestijnenlaan 200A, B-3001 Leuven, Belgium
PharmaDM, Ambachtenlaan 54D, B-3001 Leuven, Belgium
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.