Options
Named Entity Recognition with Combinations of Conditional Random Fields
Klinger, Roman; Friedrich, Christoph M.; Fluck, Juliane; u. a. (2007): Named Entity Recognition with Combinations of Conditional Random Fields, in: Lynette Hirschman, Martin Krallinger, Alfonso Valencia, u. a. (Hrsg.), Proceedings of the Second BioCreative Challenge Evaluation Workshop, Madrid, Spain, S. 89–91, doi: 10.5281/zenodo.4274543.
Faculty/Chair:
Title of the compilation:
Proceedings of the Second BioCreative Challenge Evaluation Workshop
Editors:
Hirschman, Lynette
Krallinger, Martin
Valencia, Alfonso
Corporate Body:
Centro Nacional de Investigaciones Oncologicas, CNIO
Conference:
Second BioCreative Challenge Evaluation Workshop
Publisher Information:
Year of publication:
2007
Pages:
Language:
English
Abstract:
The Gene Mention task is a Named Entity Recognition (NER) task for labeling gene and gene product names in biomedical text. To deal with acceptable alternatives additionally to the gold standard, we use combinations of Conditional Random Fields (CRF) together with a normalizing tagger. This process isfollowed by a postprocessing step including an acronym disambiguation based on Latent Semantic Analysis(LSA). For robust model selection we apply 50-fold Bootstrapping to obtain an average F-Score of 84.58 % on the trainingset and 86.33 % on the test set.
GND Keywords: ; ; ;
Named Entity Recognition
Zufälliges Feld
Text Mining
Data Mining
Keywords: ; ; ; ;
named entity recognition
text mining
data mining
conditional random fields
multi model approach
DDC Classification:
RVK Classification:
International Distribution:
Yes:
Type:
Conferenceobject
Activation date:
March 11, 2024
Versioning
Question on publication
Permalink
https://fis.uni-bamberg.de/handle/uniba/94007