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Chemical named entities recognition: a review on approaches and applications
The rapid increase in the flow rate of published digital information in all disciplines has resulted in a pressing need for techniques that can simplify the use of this information. The chemistry literature is very rich with information about chemical entities. Extracting molecules and their related...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4022577/ https://www.ncbi.nlm.nih.gov/pubmed/24834132 http://dx.doi.org/10.1186/1758-2946-6-17 |
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author | Eltyeb, Safaa Salim, Naomie |
author_facet | Eltyeb, Safaa Salim, Naomie |
author_sort | Eltyeb, Safaa |
collection | PubMed |
description | The rapid increase in the flow rate of published digital information in all disciplines has resulted in a pressing need for techniques that can simplify the use of this information. The chemistry literature is very rich with information about chemical entities. Extracting molecules and their related properties and activities from the scientific literature to “text mine” these extracted data and determine contextual relationships helps research scientists, particularly those in drug development. One of the most important challenges in chemical text mining is the recognition of chemical entities mentioned in the texts. In this review, the authors briefly introduce the fundamental concepts of chemical literature mining, the textual contents of chemical documents, and the methods of naming chemicals in documents. We sketch out dictionary-based, rule-based and machine learning, as well as hybrid chemical named entity recognition approaches with their applied solutions. We end with an outlook on the pros and cons of these approaches and the types of chemical entities extracted. |
format | Online Article Text |
id | pubmed-4022577 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40225772014-05-16 Chemical named entities recognition: a review on approaches and applications Eltyeb, Safaa Salim, Naomie J Cheminform Review The rapid increase in the flow rate of published digital information in all disciplines has resulted in a pressing need for techniques that can simplify the use of this information. The chemistry literature is very rich with information about chemical entities. Extracting molecules and their related properties and activities from the scientific literature to “text mine” these extracted data and determine contextual relationships helps research scientists, particularly those in drug development. One of the most important challenges in chemical text mining is the recognition of chemical entities mentioned in the texts. In this review, the authors briefly introduce the fundamental concepts of chemical literature mining, the textual contents of chemical documents, and the methods of naming chemicals in documents. We sketch out dictionary-based, rule-based and machine learning, as well as hybrid chemical named entity recognition approaches with their applied solutions. We end with an outlook on the pros and cons of these approaches and the types of chemical entities extracted. BioMed Central 2014-04-28 /pmc/articles/PMC4022577/ /pubmed/24834132 http://dx.doi.org/10.1186/1758-2946-6-17 Text en Copyright © 2014 Eltyeb and Salim; licensee Chemistry Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Review Eltyeb, Safaa Salim, Naomie Chemical named entities recognition: a review on approaches and applications |
title | Chemical named entities recognition: a review on approaches and applications |
title_full | Chemical named entities recognition: a review on approaches and applications |
title_fullStr | Chemical named entities recognition: a review on approaches and applications |
title_full_unstemmed | Chemical named entities recognition: a review on approaches and applications |
title_short | Chemical named entities recognition: a review on approaches and applications |
title_sort | chemical named entities recognition: a review on approaches and applications |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4022577/ https://www.ncbi.nlm.nih.gov/pubmed/24834132 http://dx.doi.org/10.1186/1758-2946-6-17 |
work_keys_str_mv | AT eltyebsafaa chemicalnamedentitiesrecognitionareviewonapproachesandapplications AT salimnaomie chemicalnamedentitiesrecognitionareviewonapproachesandapplications |