Tabular data often refers to data that is organized in a table with rows and columns. We
observe that this data format is widely used on the Web and within enterprise data …

The discovery of new materials has a documented history of propelling human progress for
centuries and more. The behaviour of a material is a function of its composition, structure …

A crucial component in the curation of KB for a scientific domain (eg, materials science,
foods & nutrition, fuels) is information extraction from tables in the domain's published …

Making health data available for secondary use enables innovative data-driven medical
research. Since modern machine learning (ML) methods and precision medicine require …

Tables are a popular and efficient means of presenting structured information. They are
used extensively in various kinds of documents including web pages. Tables display …

Tables are one of the prevalent means of organising and representing structured data. They
contain a wealth of valuable information that is challenging to extract automatically, yet can …

Tables are commonly used for structuring and consolidating knowledge, significantly
enhancing the efficiency for human readers to acquire relevant information. However, due to …

With the development of Open Data, a large number of data sources are made available to
communities (including data scientists and data analysts). This data is the treasure of digital …

We introduce TabTransformer, a new tabular data modeling architecture based on deep self-
attention Transformers. Our model works by embedding categorical features in a robust and …

The Web stores a large volume of web-tables with semi-structured data. The Semantic Web
community considers them as a valuable source for the knowledge graph population …