Learning recursion with iterative bootstrap induction

• Type: Article in International Scientific Journal
• Date: 1995

Authors

Jorge, A (Author) FEP; Brazdil, P (Author) FEP

Journal

Title: Lecture Notes in Computer Science

Vol. 100

Pages: 299-302

ISSN: 0302-9743

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 0 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-001-HVE

DOI: 10.1007/3-540-59286-5_72

Abstract (EN): In this paper we are concerned with the problem of inducing recursive Horn clauses from small sets of training examples. The method of iterative bootstrap induction is presented. In the first step, the system generates simple clauses, which can be regarded as properties of the required definition. Properties represent generalizations of the positive examples, simulating the effect of having larger number of examples. Properties are used subsequently to induce the required recursive definitions. This paper describes the method together with a series of experiments. The results support the thesis that iterative bootstrap induction is indeed an effective technique that could be of general use in ILP.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4