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 …

The pervasive use of electronic health databases has increased the accessibility of free-text
clinical reports for supplementary use. Several text classification approaches, such as …

Abstract The rise of “Big Data” analytics over unstructured text has led to renewed interest in
information extraction (IE). We surveyed the landscape of IE technologies and identified a …

Since the late 1970s, relational database technology has been adopted by most
organizations to store their essential data. However, nowadays, the needs of these …

Named-entity recognition (NER) is an important task required in a wide variety of
applications. While rule-based systems are appealing due to their well-known …

Objectives The role of social media in biomedical knowledge mining, including clinical,
medical and healthcare informatics, prescription drug abuse epidemiology and drug …

Nowadays, most openly available knowledge bases (KBs) are incomplete, since they are
not synchronized with the emerging facts happening in the real world. Therefore, knowledge …

An intrinsic part of information extraction is the creation and manipulation of relations
extracted from text. In this article, we develop a foundational framework where the central …

Rule-based information extraction is an important approach for processing the increasingly
available amount of unstructured data. The manual creation of rule-based applications is a …

Researchers have approached knowledge-base construction (KBC) with a wide range of
data resources and techniques. The authors present Elementary, a prototype KBC system …