Learning Restricted Deterministic Regular Expressions with Counting

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.