Probabilistic Pattern Matching and the Evolution of Stochastic Regular Expressions
Applied Intelligence
Regular Expression Matching in Reconfigurable Hardware
Journal of Signal Processing Systems
Creating regular expressions as mRNA motifs with GP to predict human exon splitting
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Regular expression learning for information extraction
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
BibPro: A Citation Parser Based on Sequence Alignment
IEEE Transactions on Knowledge and Data Engineering
Automatic string replace by examples
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Learning regular expressions to template-based FAQ retrieval systems
Knowledge-Based Systems
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We explore the practical feasibility of a system based on genetic programming (GP) for the automatic generation of regular expressions. The user describes the desired task by providing a set of labeled examples, in the form of text lines. The system uses these examples for driving the evolutionary search towards a regular expression suitable for the specified task. Usage of the system should require neither familiarity with GP nor with regular expressions syntax. In our GP implementation each individual represents a syntactically correct regular expression. We performed an experimental evaluation on two different extraction tasks applied to real-world datasets and obtained promising results in terms of precision and recall, even in comparison to an earlier state-of-the-art proposal.