Web tables form a valuable source of relational data. The Web contains an estimated 154
million HTML tables of relational data, with Wikipedia alone containing 1.6 million high …

Enterprises have a growing need to identify relevant tables in data lakes; eg tables that are
unionable, joinable, or subsets of each other. Tabular neural models can be helpful for such …

General solutions to augment Knowledge Graphs (KGs) with facts extracted from Web tables
aim to associate pairs of columns from the table with a KG relation based on the matches …

In this lecture we will discuss and introduce challenges of integrating openly available Web
data and how to solve them. Firstly, while we will address this topic from the viewpoint of …

Tables in documents are a widely-available and rich source of information, but not yet well-
utilised computationally because of the difficulty in automatically extracting their structure …

In this paper, we examine the possibility of using data collected from millions of tables on the
Web to extend an ontology with new attributes. There are two major challenges in using …

E very sizeable organization maintains and processes numerous data assets. The ability to
extract insights from data and leverage them for successfully completing downstream tasks …

The increase in our ability to collect and store data has led to an explosion in the number of
data repositories containing both public and enterprise data. While this abundance creates …

Data profiling is a research area that studies how statistics and metadata can be
automatically and efficiently extracted from datasets. While various previous work exists in …

Abstract The prevalence of Big Data in the current world, where there is an agile generation
of overwhelming amounts of data, has exceeded the capabilities of organizations to manage …