Learning regular sets from queries and counterexamples
Information and Computation
Efficient identification of regular expressions from representative examples
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
One-unambiguous regular languages
Information and Computation
Machine Learning
Machine Learning
Inference of concise DTDs from XML data
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Ambiguity in Graphs and Expressions
IEEE Transactions on Computers
On Learning Regular Expressions and Patterns Via Membership and Correction Queries
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
Algorithms for learning regular expressions from positive data
Information and Computation
Automatic string replace by examples
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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A learning algorithm is developed for a class of regular expressions equivalent to the class of all unionless unambiguous regular expressions of loop depth 2. The learner uses one representative example of the target language (where every occurrence of every loop in the target expression is unfolded at least twice) and a number of membership queries. The algorithm works in time polynomial in the length of the input example.