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Getting to Know Named Entity Recognition: Better Information Retrieval.
Zhang, Borui.
Affiliation
  • Zhang B; George A. Smathers Libraries at the University of Florida, Gainesville, Florida, USA.
Med Ref Serv Q ; 43(2): 196-202, 2024.
Article in En | MEDLINE | ID: mdl-38722609
ABSTRACT
Named entity recognition (NER) is a powerful computer system that utilizes various computing strategies to extract information from raw text input, since the early 1990s. With rapid advancement in AI and computing, NER models have gained significant attention and been serving as foundational tools across numerus professional domains to organize unstructured data for research and practical applications. This is particularly evident in the medical and healthcare fields, where NER models are essential in efficiently extract critical information from complex documents that are challenging for manual review. Despite its successes, NER present limitations in fully comprehending natural language nuances. However, the development of more advanced and user-friendly models promises to improve work experiences of professional users significantly.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Natural Language Processing / Information Storage and Retrieval Limits: Humans Language: En Journal: Med Ref Serv Q Year: 2024 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Natural Language Processing / Information Storage and Retrieval Limits: Humans Language: En Journal: Med Ref Serv Q Year: 2024 Type: Article Affiliation country: United States