POS-tags features for Protein-Protein Interaction Extraction from Biomedical Articles

Pedro Shiguihara-Juarez, Nils Murrugarra-Llerena, Alneu De Andrade Lopes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of the 2018 IEEE 25th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538654903
DOIs
StatePublished - 6 Nov 2018
Externally publishedYes
Event25th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018 - Lima, Peru
Duration: 8 Aug 201810 Aug 2018

Publication series

NameProceedings of the 2018 IEEE 25th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018

Conference

Conference25th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018
Country/TerritoryPeru
CityLima
Period8/08/1810/08/18

Keywords

  • POS-tags features
  • PPI extraction
  • Relation extraction

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