JOURNAL ARTICLE

Deep Learning in Natural Language Processing

Poma PanezaiBushra QayyumAbdul QadeerYahan Jan

Year: 2024 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

Recent breakthroughs in machine learning have provided the artificial intelligence field with the necessary capabilities to address persistent challenges. This paper provides a brief overview of deep learning, classified into three main categories: discriminative, generative, and hybrid models. Natural language processing (NLP) is one of the domains that has considerably profited from these breakthroughs. Deep learning techniques have allowed the efficient handling of many complex tasks related to natural language processing. This paper emphasizes important NLP tasks and notable projects that have used deep learning to tackle them. Despite the wide range of NLP tasks, the results show that deep learning continuously surpasses conventional methods across numerous applications.

Keywords:
Deep learning Natural language Field (mathematics) Language understanding Natural language understanding Natural (archaeology)

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Topics

Big Data and Digital Economy
Physical Sciences →  Computer Science →  Information Systems
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Machine Learning in Healthcare
Physical Sciences →  Computer Science →  Artificial Intelligence

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