The biomedical literature is growing rapidly, and the extraction of meaningful information
from the large amount of literature is increasingly important. Biomedical named entity …

Efficient access to chemical information contained in scientific literature, patents, technical
reports, or the web is a pressing need shared by researchers and patent attorneys from …

A bottleneck in efficiently connecting new materials discoveries to established literature has
arisen due to an increase in publications. This problem may be addressed by using named …

Motivation: Text mining is increasingly used to manage the accelerating pace of the
biomedical literature. Many text mining applications depend on accurate named entity …

Research publications are the major repository of scientific knowledge. However, their
unstructured and highly heterogenous format creates a significant obstacle to large-scale …

The automatic extraction of chemical information from text requires the recognition of
chemical entity mentions as one of its key steps. When develo** supervised named entity …

A significant amount of information about drug-related safety issues such as adverse effects
are published in medical case reports that can only be explored by human readers due to …

Chemical compounds and drugs are an important class of entities in biomedical research
with great potential in a wide range of applications, including clinical medicine. Locating …

Named entity recognition (NER) is an important step in biomedical information extraction
pipelines. Tools for NER should be easy to use, cover multiple entity types, be highly …

Motivation: The accurate identification of chemicals in text is important for many applications,
including computer-assisted reconstruction of metabolic networks or retrieval of information …