Query optimization in inductive logic programming by reordering literals

Query optimization is used frequently in relational database management systems. Most existing techniques axe based on reordering the relational operators, where the most selective operators are executed first. In this work we evaluate a similar approach in the context of Inductive Logic Programming (ILP). There are some important differences between relational database management systems and ILP systems. We describe some of these differences and list the resulting requirements for a reordering transformation suitable for ILP. We propose a transformation that meets these requirements and an algorithm for estimating the computational cost of literals, which is required by the transformation. Our transformation yields a significant improvement in execution time on the Carcinogenesis data set.status: publishe