Document Type

Conference Proceeding

Publisher

IEEE

Faculty

Computing, Health and Science

School

Computer and Information Science

RAS ID

1893

Comments

This conference paper was originally published as: Hingston, P. F. (2001). Inference of regular languages using model simplicity. Proceedings of 2001 Australian Computer Science Conference. (pp. 69-76). Gold Coast, QLD. IEEE. Original article available here

© 2001 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Abstract

We describe an approach that is related to a number of existing algorithms for the inference of a regular language from a set of positive (and optionally also negative) examples. Variations on this approach provide a family of algorithms that attempt to minimise the complexity of a description of the example data in terms of a finite state automaton model. Experiments using a standard set of small problems show that this approach produces satisfactory results when positive examples only are given, and can be helpful when only a limited number of negative examples is available. The results also suggest that improved algorithms will be needed in order to tackle more challenging problems, such as data mining and exploratory sequential analysis applications

DOI

10.1109/ACSC.2001.906625

Access Rights

free_to_read

 
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Link to publisher version (DOI)

10.1109/ACSC.2001.906625