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MedEvi: Retrieving textual evidence of relations between biomedical concepts from Medline

Summary: Search engines running on MEDLINE abstracts have been widely used by biologists to find publications that are related to their research. The existing search engines such as PubMed, however, have limitations when applied for the task of seeking textual evidence of relations between given con...

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Detalles Bibliográficos
Autores principales: Kim, Jung-jae, Pȩzik, Piotr, Rebholz-Schuhmann, Dietrich
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2387223/
https://www.ncbi.nlm.nih.gov/pubmed/18400773
http://dx.doi.org/10.1093/bioinformatics/btn117
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author Kim, Jung-jae
Pȩzik, Piotr
Rebholz-Schuhmann, Dietrich
author_facet Kim, Jung-jae
Pȩzik, Piotr
Rebholz-Schuhmann, Dietrich
author_sort Kim, Jung-jae
collection PubMed
description Summary: Search engines running on MEDLINE abstracts have been widely used by biologists to find publications that are related to their research. The existing search engines such as PubMed, however, have limitations when applied for the task of seeking textual evidence of relations between given concepts. The limitations are mainly due to the problem that the search engines do not effectively deal with multi-term queries which may imply semantic relations between the terms. To address this problem, we present MedEvi, a novel search engine that imposes positional restriction on occurrences matching multi-term queries, based on the observation that terms with semantic relations which are explicitly stated in text are not found too far from each other. MedEvi further identifies additional keywords of biological and statistical significance from local context of matching occurrences in order to help users reformulate their queries for better results. Availability: http://www.ebi.ac.uk/tc-test/textmining/medevi/ Contact: kim@ebi.ac.uk
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spelling pubmed-23872232009-02-25 MedEvi: Retrieving textual evidence of relations between biomedical concepts from Medline Kim, Jung-jae Pȩzik, Piotr Rebholz-Schuhmann, Dietrich Bioinformatics Applications Notes Summary: Search engines running on MEDLINE abstracts have been widely used by biologists to find publications that are related to their research. The existing search engines such as PubMed, however, have limitations when applied for the task of seeking textual evidence of relations between given concepts. The limitations are mainly due to the problem that the search engines do not effectively deal with multi-term queries which may imply semantic relations between the terms. To address this problem, we present MedEvi, a novel search engine that imposes positional restriction on occurrences matching multi-term queries, based on the observation that terms with semantic relations which are explicitly stated in text are not found too far from each other. MedEvi further identifies additional keywords of biological and statistical significance from local context of matching occurrences in order to help users reformulate their queries for better results. Availability: http://www.ebi.ac.uk/tc-test/textmining/medevi/ Contact: kim@ebi.ac.uk Oxford University Press 2008-06-01 2008-04-09 /pmc/articles/PMC2387223/ /pubmed/18400773 http://dx.doi.org/10.1093/bioinformatics/btn117 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Kim, Jung-jae
Pȩzik, Piotr
Rebholz-Schuhmann, Dietrich
MedEvi: Retrieving textual evidence of relations between biomedical concepts from Medline
title MedEvi: Retrieving textual evidence of relations between biomedical concepts from Medline
title_full MedEvi: Retrieving textual evidence of relations between biomedical concepts from Medline
title_fullStr MedEvi: Retrieving textual evidence of relations between biomedical concepts from Medline
title_full_unstemmed MedEvi: Retrieving textual evidence of relations between biomedical concepts from Medline
title_short MedEvi: Retrieving textual evidence of relations between biomedical concepts from Medline
title_sort medevi: retrieving textual evidence of relations between biomedical concepts from medline
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2387223/
https://www.ncbi.nlm.nih.gov/pubmed/18400773
http://dx.doi.org/10.1093/bioinformatics/btn117
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