Deep Neural Network and Text Processing: A Literature Review

Hussam Abdulla; Asim Mohammed Eltahir; Saleh Alwahaishi; Khalifa Saghair; Jan Platos; Vaclav Snasel

doi:10.1109/CSCC55931.2022.00033

Deep Neural Network and Text Processing: A Literature Review

Hussam Abdulla
, Asim Mohammed Eltahir
, Saleh Alwahaishi
, Khalifa Saghair
, Jan Platos
, Vaclav Snasel

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Deep learning is a powerful representation training algorithm which has been used to understand context clues. This paper has provided review of past research on neural networks in their use of in text analysis. Neural networks were observed to use a number of computational layers to understand hierarchical representations of the data, resulting in cutting edge results in a range of domains. This article carried out an empirical assessment of vital deep learning related techniques and frameworks to investigate their use in varied NLP tasks, as well as contextualizing, making comparisons, and comparing the various models and gives a clear knowledge of the relevant facets of deep neural network use in NLP.

Original language	English
Title of host publication	Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	139-144
Number of pages	6
ISBN (Electronic)	9781665481861
DOIs	https://doi.org/10.1109/CSCC55931.2022.00033
State	Published - 2022
Externally published	Yes
Event	26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022 - Crete, Greece Duration: 19 Jul 2022 → 22 Jul 2022

Publication series

Name	Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022

Conference

Conference	26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022
Country/Territory	Greece
City	Crete
Period	19/07/22 → 22/07/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

Artificial Intelligence (AI)
Bilingual Evaluation Understudy (BLEU)
Computational Linguistics (CL)
Computer Science (CS)
Convolutional Neural Network (CNN)
Deep Learning (DL)
Deep learning
Image Processing (IP)
Metric for Evaluation for Translation (METEOR)
Multimodal Processing (MP)
NLP
Named Entity Recognition (NER)
Natural Language Processing (NLP)
Query Answering System (QAS)
Semantically Distributed Representations (SDR)
deep neural network
denoising autoencoder (DAE)
denoising deep neural network (DDNN)
systematic review
text processing

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Signal Processing
Information Systems and Management
Electrical and Electronic Engineering
Safety, Risk, Reliability and Quality
Media Technology

Access to Document

10.1109/CSCC55931.2022.00033

Cite this

Abdulla, H., Eltahir, A. M., Alwahaishi, S., Saghair, K., Platos, J., & Snasel, V. (2022). Deep Neural Network and Text Processing: A Literature Review. In Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022 (pp. 139-144). (Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSCC55931.2022.00033

Abdulla, Hussam ; Eltahir, Asim Mohammed ; Alwahaishi, Saleh et al. / Deep Neural Network and Text Processing : A Literature Review. Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 139-144 (Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022).

@inproceedings{45699a6e9b5a4854abe2a59b27e63ffa,

title = "Deep Neural Network and Text Processing: A Literature Review",

abstract = "Deep learning is a powerful representation training algorithm which has been used to understand context clues. This paper has provided review of past research on neural networks in their use of in text analysis. Neural networks were observed to use a number of computational layers to understand hierarchical representations of the data, resulting in cutting edge results in a range of domains. This article carried out an empirical assessment of vital deep learning related techniques and frameworks to investigate their use in varied NLP tasks, as well as contextualizing, making comparisons, and comparing the various models and gives a clear knowledge of the relevant facets of deep neural network use in NLP.",

keywords = "Artificial Intelligence (AI), Bilingual Evaluation Understudy (BLEU), Computational Linguistics (CL), Computer Science (CS), Convolutional Neural Network (CNN), Deep Learning (DL), Deep learning, Image Processing (IP), Metric for Evaluation for Translation (METEOR), Multimodal Processing (MP), NLP, Named Entity Recognition (NER), Natural Language Processing (NLP), Query Answering System (QAS), Semantically Distributed Representations (SDR), deep neural network, denoising autoencoder (DAE), denoising deep neural network (DDNN), systematic review, text processing",

author = "Hussam Abdulla and Eltahir, \{Asim Mohammed\} and Saleh Alwahaishi and Khalifa Saghair and Jan Platos and Vaclav Snasel",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022 ; Conference date: 19-07-2022 Through 22-07-2022",

year = "2022",

doi = "10.1109/CSCC55931.2022.00033",

language = "English",

series = "Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022",

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}

Abdulla, H, Eltahir, AM, Alwahaishi, S, Saghair, K, Platos, J & Snasel, V 2022, Deep Neural Network and Text Processing: A Literature Review. in Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022. Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022, Institute of Electrical and Electronics Engineers Inc., pp. 139-144, 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022, Crete, Greece, 19/07/22. https://doi.org/10.1109/CSCC55931.2022.00033

Deep Neural Network and Text Processing: A Literature Review. / Abdulla, Hussam; Eltahir, Asim Mohammed; Alwahaishi, Saleh et al.
Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 139-144 (Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Deep Neural Network and Text Processing

T2 - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022

AU - Abdulla, Hussam

AU - Eltahir, Asim Mohammed

AU - Alwahaishi, Saleh

AU - Saghair, Khalifa

AU - Platos, Jan

AU - Snasel, Vaclav

PY - 2022

Y1 - 2022

N2 - Deep learning is a powerful representation training algorithm which has been used to understand context clues. This paper has provided review of past research on neural networks in their use of in text analysis. Neural networks were observed to use a number of computational layers to understand hierarchical representations of the data, resulting in cutting edge results in a range of domains. This article carried out an empirical assessment of vital deep learning related techniques and frameworks to investigate their use in varied NLP tasks, as well as contextualizing, making comparisons, and comparing the various models and gives a clear knowledge of the relevant facets of deep neural network use in NLP.

AB - Deep learning is a powerful representation training algorithm which has been used to understand context clues. This paper has provided review of past research on neural networks in their use of in text analysis. Neural networks were observed to use a number of computational layers to understand hierarchical representations of the data, resulting in cutting edge results in a range of domains. This article carried out an empirical assessment of vital deep learning related techniques and frameworks to investigate their use in varied NLP tasks, as well as contextualizing, making comparisons, and comparing the various models and gives a clear knowledge of the relevant facets of deep neural network use in NLP.

KW - Artificial Intelligence (AI)

KW - Bilingual Evaluation Understudy (BLEU)

KW - Computational Linguistics (CL)

KW - Computer Science (CS)

KW - Convolutional Neural Network (CNN)

KW - Deep Learning (DL)

KW - Deep learning

KW - Image Processing (IP)

KW - Metric for Evaluation for Translation (METEOR)

KW - Multimodal Processing (MP)

KW - NLP

KW - Named Entity Recognition (NER)

KW - Natural Language Processing (NLP)

KW - Query Answering System (QAS)

KW - Semantically Distributed Representations (SDR)

KW - deep neural network

KW - denoising autoencoder (DAE)

KW - denoising deep neural network (DDNN)

KW - systematic review

KW - text processing

UR - https://www.scopus.com/pages/publications/85147730360

U2 - 10.1109/CSCC55931.2022.00033

DO - 10.1109/CSCC55931.2022.00033

M3 - Conference contribution

AN - SCOPUS:85147730360

T3 - Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022

SP - 139

EP - 144

BT - Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 19 July 2022 through 22 July 2022

ER -

Abdulla H, Eltahir AM, Alwahaishi S, Saghair K, Platos J, Snasel V. Deep Neural Network and Text Processing: A Literature Review. In Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 139-144. (Proceedings - 26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022). doi: 10.1109/CSCC55931.2022.00033

Deep Neural Network and Text Processing: A Literature Review

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this