Abstract
Inductive Logic Programming (ILP) is a Machine Learning technique that has been quite successful in knowledge discovery for relational domains. ILP systems implemented in Prolog challenge the limits of Prolog systems due to heavy usage of resources such as database accesses and memory usage, and to very long execution times. The major reason to implement ILP systems in Prolog is that the inference mechanism implemented by the Prolog engine is fundamental to most ILP learning algorithms. ILP systems can therefore bene.t from the extensive performance improvement work that has taken place for Prolog. On the other hand, ILP is a non-classical Prolog application because it uses large sets of ground facts and requires storing a large search tree.
The work presented in this paper has been partially supported by project APRIL (Project POSI/SRI/40749/2001) and funds granted to LIACC through the Programa de Financiamento Plurianual, Fundaçã o para a Ciência e Tecnologia and Programa POSI. Nuno Fonseca is funded by the FCT grant SFRH/BD/7045/2001.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Fonseca, N., Silva, F., Camacho, R., Costa, V.S.: Induction with April - A preliminary report. Technical report, DCC-FC & LIACC, UP (2003)
Muggleton, S., De Raedt, L.: Inductive logic programming: Theory and methods. Journal of Logic Programming 19/20, 629–679 (1994)
Nienhuys-Cheng, S.-H., de Wolf, R. (eds.): Foundations of Inductive Logic Programming. LNCS(LNAI), vol. 1228. Springer, Heidelberg (1997)
Fonseca, N., Costa, V.S., Silva, F., Camacho, R.: On the implementation of an ilp system with prolog. Technical report, DCC-FC & LIACC, UP (2003)
Cussens, J.: Part-of-speech disambiguation using ilp. Technical Report PRGTR- 25-96, Oxford University Computing Laboratory (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fonseca, N., Costa, V.S., Silva, F., Camacho, R. (2003). Experimental Evaluation of a Caching Technique for ILP. In: Pires, F.M., Abreu, S. (eds) Progress in Artificial Intelligence. EPIA 2003. Lecture Notes in Computer Science(), vol 2902. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24580-3_22
Download citation
DOI: https://doi.org/10.1007/978-3-540-24580-3_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20589-0
Online ISBN: 978-3-540-24580-3
eBook Packages: Springer Book Archive