Deep Learning vs Compression-Based vs Traditional Machine Learning Classifiers to Detect Hadith Authenticity

Tarmom, T orcid.org/0000-0002-2834-461X, Atwell, E and Alsalka, M (2022) Deep Learning vs Compression-Based vs Traditional Machine Learning Classifiers to Detect Hadith Authenticity. In: Lossio-Ventura, JA, Valverde-Rebaza, J, Díaz, E, Muñante, D, Gavidia-Calderon, C, Valejo, ADB and Alatrista-Salas, H, (eds.) Information Management and Big Data. 8th International Conference on Information Management and Big Data, SIMBig 2021, 01-03 Dec 2021, Online. Communications in Computer and Information Science, 1577 . Springer , pp. 206-222. ISBN 978-3-031-04446-5

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Lossio-Ventura, JA
  • Valverde-Rebaza, J
  • Díaz, E
  • Muñante, D
  • Gavidia-Calderon, C
  • Valejo, ADB
  • Alatrista-Salas, H
Copyright, Publisher and Additional Information:

© 2022 The Author(s). This is an author produced version of a conference paper published in Information Management and Big Data. Uploaded in accordance with the publisher's self-archiving policy.

Keywords: Hadith authenticity; Hadith corpus; Deep learning; Arabic natural language processing
Dates:
  • Published: 22 April 2022
  • Published (online): 20 April 2022
  • Accepted: 20 November 2021
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 11 Apr 2022 12:21
Last Modified: 14 Nov 2023 20:38
Status: Published
Publisher: Springer
Series Name: Communications in Computer and Information Science
Identification Number: 10.1007/978-3-031-04447-2_14
Open Archives Initiative ID (OAI ID):

Export

Statistics