Paper Info
Title
BANNER: an executable survey of advances in biomedical named entity recognition.
Abstract
There has been an increasing amount of research on biomedical named entity recognition, the most basic text extraction problem, resulting in significant progress by different research teams around the world. This has created a need for a freely-available, open source system implementing the advances described in the literature. In this paper we present BANNER, an open-source, executable survey of advances in biomedical named entity recognition, intended to serve as a benchmark for the field. BANNER is implemented in Java as a machine-learning system based on conditional random fields and includes a wide survey of the best techniques recently described in the literature. It is designed to maximize domain independence by not employing brittle semantic features or rule-based processing steps, and achieves significantly better performance than existing baseline systems. It is therefore useful to developers as an extensible NER implementation, to researchers as a standard for comparing innovative techniques, and to biologists requiring the ability to find novel entities in large amounts of text.
Year
Venue
Keywords
2008
Pacific Symposium on Biocomputing
rule based,conditional random field,machine learning
Field
DocType
ISSN
Conditional random field,World Wide Web,Domain independence,Computer science,Download,Banner,Named-entity recognition,Java,Executable
Conference
2335-6936
Citations 
PageRank 
References 
194
7.51
16
Authors
2
Search Limit
100194
Name
Order
Citations
PageRank
Robert Leaman191439.98
Graciela Gonzalez262439.60