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 …

The volume of published biomedical research, and therefore the underlying biomedical
knowledge base, is expanding at an increasing rate. Among the tools that can aid …

Motivation Text mining has become an important tool for biomedical research. The most
fundamental text-mining task is the recognition of biomedical named entities (NER), such as …

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 …

This survey covers fifteen years of research in the Named Entity Recognition and
Classification (NERC) field, from 1991 to 2006. We report observations about languages …

With biomedical literature increasing at a rate of several thousand papers per week, it is
impossible to keep abreast of all developments; therefore, automated means to manage the …

Sophisticated information technologies are needed for effective data acquisition and
integration from a growing body of the biomedical literature. Successful term identification is …

Background We present a model for tagging gene and protein mentions from text using the
probabilistic sequence tagging framework of conditional random fields (CRFs). Conditional …

The rapid increase in the flow rate of published digital information in all disciplines has
resulted in a pressing need for techniques that can simplify the use of this information. The …

The biomedical community makes extensive use of text mining technology. In the past
several years, enormous progress has been made in developing tools and methods, and the …