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 …

In document-oriented databases, schema is a soft concept and the documents in a collection
can be stored using different local schemata. This gives designers and implementers …

Curated databases are databases that are populated and updated with a great deal of
human effort. Most reference works that one traditionally found on the reference shelves of …

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

The variety feature of Big Data, represented by multi-model data, has brought a new
dimension of complexity to all aspects of data management. The need to process a set of …

We investigate the problem of learning join queries from user examples. The user is
presented with a set of candidate tuples and is asked to label them as positive or negative …

Machine translation has wide applications in daily life. In mission-critical applications such
as translating official documents, incorrect translation can have unpleasant or sometimes …

Roughly every third Wikipedia article contains an infobox-a table that displays important
facts about the subject in attribute-value form. The schema of an infobox, ie, the attributes …

Automatically generating regular expressions (abbrev. regexes) from natural language
description (NL2RE) has been an emerging research area. Prior studies treat regex as a …

The rise of data platforms has enabled the collection and processing of huge volumes of
data, but has opened to the risk of losing their control. Collecting proper metadata about raw …