Machine Reading of Biological Texts - Bacteria-Biotope Extraction

Wouter Massa, Parisa Kordjamshidi, Thomas Provoost, Marie-Francine Moens

Abstract

The tremendous amount of scientific literature available about bacteria and their biotopes underlines the need for efficient mechanisms to automatically extract this information. This paper presents a system to extract the bacteria and their habitats, as well as the relations between them. We investigate to what extent current techniques are suited for this task and test a variety of models in this regard. To detect entities in a biological text we use a linear chain Conditional Random Field (CRF). For the prediction of relations between the entities, a model based on logistic regression is built. Designing a system upon these techniques, we explore several improvements for both the generation and selection of good candidates. One contribution to this lies in the extended flexibility of our ontology mapper, allowing for a more advanced boundary detection. Furthermore, we discover value in the combination of several distinct candidate generation rules. Using these techniques, we show results that are significantly improving upon the state of art for the BioNLP Bacteria Biotopes task.

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Paper Citation


in Harvard Style

Massa W., Kordjamshidi P., Provoost T. and Moens M. (2015). Machine Reading of Biological Texts - Bacteria-Biotope Extraction . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015) ISBN 978-989-758-070-3, pages 55-64. DOI: 10.5220/0005214700550064


in Bibtex Style

@conference{bioinformatics15,
author={Wouter Massa and Parisa Kordjamshidi and Thomas Provoost and Marie-Francine Moens},
title={Machine Reading of Biological Texts - Bacteria-Biotope Extraction},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015)},
year={2015},
pages={55-64},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005214700550064},
isbn={978-989-758-070-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015)
TI - Machine Reading of Biological Texts - Bacteria-Biotope Extraction
SN - 978-989-758-070-3
AU - Massa W.
AU - Kordjamshidi P.
AU - Provoost T.
AU - Moens M.
PY - 2015
SP - 55
EP - 64
DO - 10.5220/0005214700550064