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

• DOI: 10.1613/jair.924
• Publication Date: 2018-07-12T13:11:50Z
• Authors: H. Blockeel; L. Dehaspe; B. Demoen; G. Janssens; J. Ramon; H. Vandecasteele
• Keywords: FOS: Computer and information sciences; Artificial Intelligence (cs.AI); Computer Science - Artificial Intelligence; 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; discovery

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.