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Biomedical text disambiguation using UMLS

Authors:

Wessam Gad El-Rab,

Osmar R. Zaïane,

Mohammad El-HajjAuthors Info & Claims

ASONAM '13: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

Pages 943 - 947

https://doi.org/10.1145/2492517.2500251

Published: 25 August 2013 Publication History

Abstract

Interest in extracting information from biomedical documents has increased significantly in recent years but has always been challenged by the ambiguity of natural language. An important source of ambiguity is the usage of polysemous words: words with multiple meanings. Word sense disambiguation algorithms attempt to solve this problem by finding the correct meaning of a polysemous word in a given context, but very few algorithms were designed to disambiguate biomedical text. In this study we propose a word sense disambiguation algorithm focused on biomedical text. The proposed algorithm does not need to be trained and uses a relatively small knowledge base.

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Cited By

Hu YNie TShen DKou YYu G(2021)An integrated pipeline model for biomedical entity alignmentFrontiers of Computer Science10.1007/s11704-020-8426-415:3Online publication date: 16-Jan-2021
https://doi.org/10.1007/s11704-020-8426-4
Jing X(2020)UMLS at 30 years: How it is used and published (Preprint)JMIR Medical Informatics10.2196/20675Online publication date: 25-May-2020
https://doi.org/10.2196/20675
Bentounsi IBoufaïda Z(2018)Disambiguation of semantic types in complex noun phrases for extracting candidate termsInternational Journal of Metadata, Semantics and Ontologies10.1504/IJMSO.2015.07083010:2(112-122)Online publication date: 16-Dec-2018
https://dl.acm.org/doi/10.1504/IJMSO.2015.070830
Show More Cited By

Index Terms

Biomedical text disambiguation using UMLS

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cover image ACM Conferences

ASONAM '13: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

August 2013

1558 pages

ISBN:9781450322409

DOI:10.1145/2492517

General Chairs:
Jon Rokne
University of Calgary, Calgary, AB, Canada
,
Christos Faloutsos
Carnegie Mellon University, Pittsburgh, PA

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 25 August 2013

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ASONAM '13

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ASONAM '13: Advances in Social Networks Analysis and Mining 2013

August 25 - 28, 2013

Ontario, Niagara, Canada

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Overall Acceptance Rate 116 of 549 submissions, 21%

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Cited By

Hu YNie TShen DKou YYu G(2021)An integrated pipeline model for biomedical entity alignmentFrontiers of Computer Science10.1007/s11704-020-8426-415:3Online publication date: 16-Jan-2021
https://doi.org/10.1007/s11704-020-8426-4
Jing X(2020)UMLS at 30 years: How it is used and published (Preprint)JMIR Medical Informatics10.2196/20675Online publication date: 25-May-2020
https://doi.org/10.2196/20675
Bentounsi IBoufaïda Z(2018)Disambiguation of semantic types in complex noun phrases for extracting candidate termsInternational Journal of Metadata, Semantics and Ontologies10.1504/IJMSO.2015.07083010:2(112-122)Online publication date: 16-Dec-2018
https://dl.acm.org/doi/10.1504/IJMSO.2015.070830
Kumaravel RSelvaraj SMala C(2018)A Multidomain Layered Approach in Development of Industrial Ontology to Support Domain Identification for Unstructured TextIEEE Transactions on Industrial Informatics10.1109/TII.2018.283556714:9(4033-4044)Online publication date: Sep-2018
https://doi.org/10.1109/TII.2018.2835567

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