Semantic Search for Biomedical Texts using Predicate-Argument Structure

Mohammed Alliheedi, Robert E. Mercer

2020

Abstract

In this position paper we argue that using semantic roles in addition to using biologically-oriented ontologies and databases (or knowledge bases) will further enhance the generation of RDF triples that can be collected from biomedical text. RDF triples have been used to enhance semantic search beyond the simple use of linguistically oriented additions such as synonyms. We wish to focus on drug-virus interactions.

Paper Citation

in Harvard Style

Alliheedi M. and Mercer R. (2020). Semantic Search for Biomedical Texts using Predicate-Argument Structure. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 2: KEOD; ISBN 978-989-758-474-9, SciTePress, pages 299-306. DOI: 10.5220/0010150702990306

in Bibtex Style

@conference{keod20,
author={Mohammed Alliheedi and Robert E. Mercer},
title={Semantic Search for Biomedical Texts using Predicate-Argument Structure},
booktitle={Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 2: KEOD},
year={2020},
pages={299-306},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010150702990306},
isbn={978-989-758-474-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 2: KEOD
TI - Semantic Search for Biomedical Texts using Predicate-Argument Structure
SN - 978-989-758-474-9
AU - Alliheedi M.
AU - Mercer R.
PY - 2020
SP - 299
EP - 306
DO - 10.5220/0010150702990306
PB - SciTePress