The ubiquity of data lakes has created fascinating new challenges for data management
research. In this tutorial, we review the state-of-the-art in data management for data lakes …

Tables are probably the most natural way to represent relational data in various media and
formats. They store a large number of valuable facts that could be utilized for question …

Structure information extraction refers to the task of extracting structured text fields from web
pages, such as extracting a product offer from a shop** page including product title …

Existing techniques for unionable table search define unionability using metadata (tables
must have the same or similar schemas) or column-based metrics (for example, the values …

Dataset discovery from data lakes is essential in many real application scenarios. In this
paper, we propose Starmie, an end-to-end framework for dataset discovery from data lakes …

Tables are pervasive on the Web. Informative web tables range across a large variety of
topics, which can naturally serve as a significant resource to satisfy user information needs …

The task of web information extraction is to extract target fields of an object from web pages,
such as extracting the name, genre and actor from a movie page. Recent sequential …

Search and information retrieval systems are becoming more expressive in interpreting user
queries beyond the traditional weighted bag-of-words model of document retrieval. For …

Ground is an open-source data context service, a system to manage all the information that
informs the use of data. Data usage has changed both philosophically and practically in the …

A “Table Extractor” provides various techniques for auto matically delimiting and extracting
tables from arbitrary documents. In various implementations, the Table extractor also …