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Authors: Wouter Massa 1 ; Parisa Kordjamshidi 2 ; Thomas Provoost 1 and Marie-Francine Moens 1

Affiliations: 1 KU Leuven, Belgium ; 2 University of Illinois at Urbana-Champaign and KU Leuven, United States

ISBN: 978-989-758-070-3

Keyword(s): Natural Language Processing, Text Mining, Relation Extraction, BioNLP, Bioinformatics, Bacteria, Bacteria Biotopes.

Related Ontology Subjects/Areas/Topics: Algorithms and Software Tools ; Bioinformatics ; Biomedical Engineering ; Data Mining and Machine Learning ; Pattern Recognition, Clustering and Classification

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 r esults that are significantly improving upon the state of art for the BioNLP Bacteria Biotopes task. (More)

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Paper citation in several formats:
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

@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},
}

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

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