Profiling data to determine metadata about a given dataset is an important and frequent
activity of any IT professional and researcher and is necessary for various use-cases. It …

The problem of inducing, learning or inferring grammars has been studied for decades, but
only in recent years has grammatical inference emerged as an independent field with …

Regular expressions have served as the dominant workhorse of practical information
extraction for several years. However, there has been little work on reducing the manual …

A large class of entity extraction tasks from text that is either semistructured or fully
unstructured may be addressed by regular expressions, because in many practical cases …

We develop a penalized likelihood estimation framework to learn the structure of Gaussian
Bayesian networks from observational data. In contrast to recent methods which accelerate …

One of the key properties of a program is its input specification. Having a formal input
specification can be critical in fields such as vulnerability analysis, reverse engineering …

Regular expressions are widely used within and even outside of computer science due to
their expressiveness and flexibility. However, regular expressions have a quite compact and …

We present a method for synthesizing regular expressions for introductory automata
assignments. Given a set of positive and negative examples, the method automatically …

Inferring an appropriate DTD or XML Schema Definition (XSD) for a given collection of XML
documents essentially reduces to learning deterministic regular expressions from sets of …

We consider the problem to infer a concise Document Type Definition (DTD) for a given set
of XML-documents, a problem which basically reduces to learning of concise regular …