Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs

Details Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs

2011-06-09

arxiv.org/abs/1106.1803v1

Journal Of Artificial Intelligence Research, Volume 16, pages 135-166, 2002

Computer Science

Artificial Intelligence

Scientific paper

10.1613/jair.924

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.

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