An automata based approach to biomedical named entity recognition

Dowdall, James, Keller, Bill, Padro, Lluis and Padro, Muntsa (2007) An automata based approach to biomedical named entity recognition. In: Annual Meeting of the ISMB BioLINK Special Interest Group on Text Data Mining, Vienna, Austria.

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Abstract

ing an automata learning algorithm: Causal-State Splitting Reconstruction
[1]. This algorithm has previously been applied to Named Entity Recognition [2]
obtaining good results given the simplicity of the approach.
The same approach has been applied to Biomedical NE identification, using
GENIA corpus 3.0, with 10-fold cross-validation. Our system attained F1 =
73.14%.
These results can be compared directly to [3] and [4], which used the same
data. First system obtains F1 = 57.4% using ME Models, and the second one reports F1 = 79.2% using SVMs. Both improve their results using post-processing
techniques, reaching F1 = 76.9% and F1 = 79.9% respectively.
Our system does not use any post-processing techniques, and takes into
acount few features, so the results are considered very promising. In future work
some post-processing will be developed to improve the results.

Item Type: Conference or Workshop Item (Paper)
Schools and Departments: School of Engineering and Informatics > Informatics
Subjects: P Language and Literature > P Philology. Linguistics > P0098 Computational linguistics. Natural language processing
Q Science > QA Mathematics > QA0075 Electronic computers. Computer science
Depositing User: Bill Keller
Date Deposited: 08 Nov 2012 15:12
Last Modified: 08 Nov 2012 15:12
URI: http://sro.sussex.ac.uk/id/eprint/41452

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