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.

This is the latest version of this item.

Full text not available from this repository.


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 =
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

Available Versions of this Item

📧 Request an update