Title
POS-tags features for Protein-Protein Interaction Extraction from Biomedical Articles
Date Issued
06 November 2018
Access level
metadata only access
Resource Type
conference paper
Author(s)
Univesity of Pittsburgh
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
Protein-Protein Interaction (PPI) extraction from biomedical articles consists on extracting sentences were two or more proteins interact. Traditional articles tackle this problem creating more sophisticated classifiers. In contrast to them, we focus on discriminative features that can be exploited by traditional classifiers. Our method exploits information from POS-tags features and are combined with a bag-of-words approach. We used five standard corpora of PPI: Aimed, Bioinfer, HPRD50, IEPA and LLL. Our method is simple and achieves high results compared with other approaches. We achieve an improvement of 11% with our best competitor.
OCDE Knowledge area
Biología
Subjects
Scopus EID
2-s2.0-85058030914
Source
Proceedings of the 2018 IEEE 25th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018
ISBN of the container
9781538654903
Sources of information:
Directorio de Producción Científica
Scopus