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 …

One effective way to improve the state of the art is through competitions. Following the
success of the Critical Assessment of protein Structure Prediction (CASP) in bioinformatics …

Generally, data is available abundantly in unlabeled form, and its annotation requires some
cost. The labeling, as well as learning cost, can be minimized by learning with the minimum …

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

Active learning is well-suited to many problems in natural language processing, where
unlabeled data may be abundant but annotation is slow and expensive. This paper aims to …

The Handbook of Natural Language Processing, Second Edition presents practical tools
and techniques for implementing natural language processing in computer systems. Along …

Named entity recognition is a crucial component of biomedical natural language processing,
enabling information extraction and ultimately reasoning over and knowledge discovery …

Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop.
In this task participants designed systems to identify substrings in sentences corresponding …

Natural language processing (NLP) and text mining technologies for the chemical domain
(ChemNLP or chemical text mining) are key to improve the access and integration of …

The automatic recognition of gene names and their associated database identifiers from
biomedical text has been widely studied in recent years, as these tasks play an important …