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An ILP refinement operator for biological grammar learning

Fredouille, DC, Bryant, CH, Jayawickreme, CK, Jupe, S and Topp, S 2007, 'An ILP refinement operator for biological grammar learning' , in: Inductive logic programming , Lecture notes in artificial intelligence (subseries of Lecture notes in computer science) (4455) , Springer, Berlin / Heidelberg, Germany, pp. 214-228.

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Abstract

We are interested in using Inductive Logic Programming (ILP) to infer grammars representing sets of biological sequences. We call these biological grammars. ILP systems are well suited to this task in the sense that biological grammars have been represented as logic programs using the Definite Clause Grammar or the String Variable Grammar formalisms. However, the speed at which ILP systems can generate biological grammars has been shown to be a bottleneck. This paper presents a novel refinement operator implementation, specialised to infer biological grammars with ILP techniques. This implementation is shown to significantly speed-up inference times compared to the use of the classical refinement operator: time gains larger than 5-fold were observed in 4/5 of the experiments, and the maximum observed gain is over 300-fold.

Item Type: Book Section
Editors: Muggleton, SH, Otero, R and Tamaddoni-Nezhad, A
Additional Information: Paper originally presented at the 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27 2006
Themes: Subjects / Themes > Q Science > QA Mathematics > QA075 Electronic computers. Computer science
Subjects / Themes > Q Science > QH Natural history > QH301 Biology
Subjects outside of the University Themes
Schools: Colleges and Schools > College of Science & Technology
Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering
Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > Data Mining and Pattern Recognition Research Centre
Publisher: Springer
Refereed: Yes
Series Name: Lecture notes in artificial intelligence (subseries of Lecture notes in computer science)
ISBN: 9783540738466
Related URLs:
Depositing User: Dr Chris H. Bryant
Date Deposited: 16 Feb 2009 13:57
Last Modified: 20 Aug 2013 15:55
URI: http://usir.salford.ac.uk/id/eprint/1754

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