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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...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2008
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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 |
format | Text |
id | pubmed-2387223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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