Semantic Search for Biomedical Texts using Predicate-Argument Structure

Mohammed Alliheedi; Robert E. Mercer

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Paper

Semantic Search for Biomedical Texts using Predicate-Argument Structure

Topics: Knowledge Representation; Natural Language Processing

In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 0IC3K, 299-306, 2020

Authors: Mohammed Alliheedi ¹ and Robert E. Mercer ²

Affiliations: ¹ Department of Computer Science, Al Baha University, Prince Mohammad Bin Saud, Al Bahah 65527, Saudi Arabia ; ² Department of Computer Science, The University of Western Ontario, 1151 Richmond St., London, Ontario, Canada

Keyword(s): Biomedical Ontology, Semantic Search, Semantic Roles, Knowledge Representation, Formal Ontology.

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.

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Paper citation in several formats:

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) - KEOD; ISBN 978-989-758-474-9; ISSN 2184-3228, SciTePress, pages 299-306. DOI: 10.5220/0010150702990306

@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) - KEOD},
year={2020},
pages={299-306},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010150702990306},
isbn={978-989-758-474-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KEOD
TI - Semantic Search for Biomedical Texts using Predicate-Argument Structure
SN - 978-989-758-474-9
IS - 2184-3228
AU - Alliheedi, M.
AU - Mercer, R.
PY - 2020
SP - 299
EP - 306
DO - 10.5220/0010150702990306
PB - SciTePress