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Learning Restricted Deterministic Regular Expressions with Counting

  • Xiaofan Wang
  • Haiming ChenEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11881)

Abstract

Regular expressions are widely used in various fields. Learning regular expressions from sequence data is still a popular topic. Since many XML documents are not accompanied by a schema, or a valid schema, learning regular expressions from XML documents becomes an essential work. In this paper, we propose a restricted subclass of single-occurrence regular expressions with counting (RCsores) and give a learning algorithm of RCsores. First, we learn a single-occurrence regular expressions (SORE). Then, we construct an equivalent countable finite automaton (CFA). Next, the CFA runs on the given finite sample to obtain an updated CFA, which contains counting operators occurring in an RCsore. Finally we transform the updated CFA to an RCsore. Moreover, our algorithm can ensure the result is a minimal generalization (such generalization is called descriptive) of the given finite sample.

Keywords

Schema inference Regular expressions Counting Descriptive generalization 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.State Key Laboratory of Computer Science, Institute of SoftwareChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina

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