Title
Efficient Learning of Regular Expressions from Good Examples
Abstract
We consider the problem of restoring regular expressions from expressive examples. We define the class of unambiguous regular expressions, the notion of the union number of an expression showing how many union operations can occur directly under any single iteration, and the notion of an expressive example. We present a polynomial time algorithm which tries to restore an unambiguous regular expression from one expressive example. We prove that if the union number of the expression is 0 or 1 and the example is long enough, then the algorithm correctly restores the original expression from one good example. The proof relies on original investigations in theory of covering symbol sequences (words) by different sets of generators. The algorithm has been implemented and we also report computer experiments which show that the proposed method is quite practical.
Year
DOI
Venue
1994
10.1007/3-540-58520-6_55
AII/ALT
Keywords
Field
DocType
good examples,efficient learning,regular expressions,regular expression,difference set,computer experiment
Inductive reasoning,Discrete mathematics,Computer experiment,Regular expression,Computer science,Symbol,Regular language,Time complexity
Conference
ISBN
Citations 
PageRank 
3-540-58520-6
9
1.58
References 
Authors
10
2
Name
Order
Citations
PageRank
Alvis Brazma11922216.42
Karlis Cerans231448.74