Abstract

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 N atural L anguage G eneration followed by presenting the history and evolution of NLP. We then discuss in detail the state of the art presenting the various applications of NLP, current trends, and challenges. Finally, we present a discussion on some available datasets, models, and evaluation metrics in NLP.

Keywords

Automatic summarizationComputer scienceNatural language processingMachine translationArtificial intelligenceQuestion answeringInformation extractionNatural language generationNatural languageTranslation (biology)State (computer science)Programming language

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Publication Info

Year
2022
Type
article
Volume
82
Issue
3
Pages
3713-3744
Citations
1514
Access
Closed

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Cite This

Diksha Khurana, Aditya Koli, Kiran Khatter et al. (2022). Natural language processing: state of the art, current trends and challenges. Multimedia Tools and Applications , 82 (3) , 3713-3744. https://doi.org/10.1007/s11042-022-13428-4

Identifiers

DOI
10.1007/s11042-022-13428-4
PMID
35855771
PMCID
PMC9281254
arXiv
1708.05148

Data Quality

Data completeness: 84%