Natural language processing: state of the art, current trends and challenges.
NLP applications
NLP evaluation metrics
Natural language generation
Natural language processing
Natural language understanding
Journal
Multimedia tools and applications
ISSN: 1380-7501
Titre abrégé: Multimed Tools Appl
Pays: United States
ID NLM: 101555932
Informations de publication
Date de publication:
2023
2023
Historique:
received:
03
02
2021
revised:
23
03
2022
accepted:
02
07
2022
pubmed:
21
7
2022
medline:
21
7
2022
entrez:
20
7
2022
Statut:
ppublish
Résumé
Natural language processing (NLP) has recently gained much attention for representing and analyzing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. In this paper, we first distinguish four phases by discussing different levels of NLP and components of
Identifiants
pubmed: 35855771
doi: 10.1007/s11042-022-13428-4
pii: 13428
pmc: PMC9281254
doi:
Types de publication
Journal Article
Langues
eng
Pagination
3713-3744Informations de copyright
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.corrected publication 2022.
Déclaration de conflit d'intérêts
Conflict of interestThe first draft of this paper was written under the supervision of Dr. Kiran Khatter and Dr. Sukhdev Singh, associated with CL- Educate: Accendere Knowledge Management Services Pvt. Ltd. and deputed at the Manav Rachna International University. The draft is also available on arxiv.org at https://arxiv.org/abs/1708.05148