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Mapping biological entities using the longest approximately common prefix method
BACKGROUND: The significant growth in the volume of electronic biomedical data in recent decades has pointed to the need for approximate string matching algorithms that can expedite tasks such as named entity recognition, duplicate detection, terminology integration, and spelling correction. The tas...
Tallennettuna:
| Päätekijät: | , , |
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| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
BioMed Central
2014
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4086698/ https://ncbi.nlm.nih.gov/pubmed/24928653 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-15-187 |
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