Efficient and Scalable Induction of Logic Programs using a Deductive Database System
Michel Ferreira, Nuno A. Fonseca, Ricardo Rocha and Tiago Soares
August 2006
Abstract
A consequence of ILP systems being implemented in Prolog or using
Prolog libraries is that, usually, these systems use a Prolog internal
database to store and manipulate data. However, in real-world
problems, the original data is rarely in Prolog format. In fact, the
data is often kept in Relational Database Management Systems (RDBMS)
and then converted to a format acceptable by the ILP
system. Therefore, a more interesting approach is to link the ILP
system to the RDBMS and manipulate the data without converting it.
This scheme has the advantage of being more scalable since the whole
data does not need to be loaded into memory by the ILP system. In this
paper we study several approaches of coupling ILP systems with RDBMS
systems and evaluate their impact on performance. We propose to use a
Deductive Database (DDB) system to transparently translate the
hypotheses to relational algebra expressions. The empirical evaluation
performed shows that the execution time of ILP algorithms can be
effectively reduced using a DDB and that the size of the problems can
be increased due to a non-memory storage of the data.
Bibtex
@InProceedings{ferreira-ilp06,
author = {M. Ferreira and N. A. Fonseca and R. Rocha and T. Soares},
title = {{Efficient and Scalable Induction of Logic Programs using a Deductive Database System}},
booktitle = {Proceedings of the 16th International Conference on Inductive Logic Programming (ILP 2006)},
pages = {184--198},
number = {4455},
series = {LNAI},
publisher = {Springer},
editor = {S. Muggleton and R. Otero and A. Tamaddoni-Nezhad},
month = {August},
year = {2006},
address = {Santiago de Compostela, Spain},
}
Download Paper
PDF file
Springer
Download Poster
PDF file