Biomedical named entity recognition using conditional random fields and rich feature sets

Authors:
Burr Settles
Affiliations:
University of Wisconsin-Madison, Madison, WI
Venue:
JNLPBA '04 Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications
Year:
2004

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Abstract

As the wealth of biomedical knowledge in the form of literature increases, there is a rising need for effective natural language processing tools to assist in organizing, curating, and retrieving this information. To that end, named entity recognition (the task of identifying words and phrases in free text that belong to certain classes of interest) is an important first step for many of these larger information management goals.