This tutorial gives an overview on state-of-the-art methods for the automatic construction of
large knowledge bases and harnessing them for data and text analytics. It covers both big …

Data mining techniques for extracting knowledge from text have been applied extensively to
applications including question answering, document summarisation, event extraction and …

Many pressing questions in science are macroscopic: they require scientists to consult
information expressed in a wide range of resources, many of which are not organized in a …

We focus on knowledge base construction (KBC) from richly formatted data. In contrast to
KBC from text or tabular data, KBC from richly formatted data aims to extract relations …

Equipping machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

Search, exploration and social experience on the Web has recently undergone tremendous
changes with search engines, web portals and social networks offering a different …

A knowledge base (KB) contains a set of concepts, instances, and relationships. Over the
past decade, numerous KBs have been built, and used to power a growing array of …

A fundamental challenge in the intersection of Artificial Intelligence and Databases consists
of developing methods to automatically manage Knowledge Bases which can serve as a …

The proliferation of knowledge-sharing communities such as Wikipedia and the progress in
scalable information extraction from Web and text sources have enabled the automatic …

Most existing knowledge graphs (KGs) in academic domains suffer from problems of
insufficient multi-relational information, name ambiguity and improper data format for large …