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Named Entity Recognition with Combinations of Conditional Random Fields
Klinger, Roman; Hofmann-Apitius, Martin; Fluck, Juliane; u. a. (2024): Named Entity Recognition with Combinations of Conditional Random Fields, in: Bamberg: Otto-Friedrich-Universität, S. 89–91.
Faculty/Chair:
Publisher Information:
Year of publication:
2024
Pages:
Source/Other editions:
Proceedings of the Second BioCreative Challenge Evaluation Workshop / Lynette Hirschman, Martin Krallinger, Alfonso Valencia (Hg.). - Madrid, Spain : Centro Nacional de Investigaciones Oncologicas, CNIO, 2007, S. 89–91.
Year of first publication:
2007
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:
August 19, 2024
Permalink
https://fis.uni-bamberg.de/handle/uniba/96533