Efficient and scalable induction of logic programs using a deductive database system

• Type: Article in International Conference Proceedings Book
• Date: 2007

Authors

Michel Ferreira (Author) FCUP; Nuno A Fonseca (Author) Other; Ricardo Rocha (Author) FCUP; Tiago Scares (Author) Other

Conference proceedings International

Title: Inductive Logic Programming

Pages: 184-198

16th International Conference on Inductive Logic Programming

Santiago de Compostela, SPAIN, AUG 24-27, 2006

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 2 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-004-DFS

DOI: 10.1007/978-3-540-73847-3_22

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15