research-article

An Exhaustive Literature Review of Hadith Text Mining

Author:

Mohamed Atef MosaAuthors Info & Claims

ACM Transactions on Asian and Low-Resource Language Information Processing, Volume 22, Issue 7

Article No.: 187, Pages 1 - 16

https://doi.org/10.1145/3588315

Published: 20 July 2023 Publication History

Abstract

The Quran and the hadith of the Prophet are the two sources of legislation for Muslims. Sharia rulings and laws are not only derived from the Quran but also the bulk of them come through hadith. Understanding the hadith, its classification, and verification of its authenticity is vital to reach detailed rulings, as the volume of the hadith is many times greater than the volume of the Quran. As a result, mining in the hadith text is one of the things that has attracted the attention of researchers in the past few years. In this study, we conducted a survey of all the techniques and systems related to the mining of the hadith in its two parts, the Al-Matn and the Al-Sanad. On the other hand, the challenges and obstacles which confronted researchers have been shown; in addition, some suggested tips were highlighted to overcome those challenges. Furthermore, the most essential modern techniques used in the classification of Arabic texts, which gave a high degree of efficiency, were highlighted as milestones for future studies.

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Cited By

Mahmoud SNabil ESaif OTorki M(2024)Narrator identification by querying Sanad graph and utilizing the NarratorsKG on AR-Sanad 280K-v2 datasetNeural Computing and Applications10.1007/s00521-024-10194-236:36(23169-23180)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s00521-024-10194-2

Index Terms

An Exhaustive Literature Review of Hadith Text Mining
1. Computing methodologies
  1. Machine learning
    1. Machine learning algorithms
2. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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Information & Contributors

Information

Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 22, Issue 7

July 2023

422 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3610376

Editor:
Imed Zitouni
Google, USA

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 July 2023

Online AM: 17 March 2023

Accepted: 13 March 2023

Revised: 24 February 2023

Received: 30 December 2022

Published in TALLIP Volume 22, Issue 7

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Cited By

Mahmoud SNabil ESaif OTorki M(2024)Narrator identification by querying Sanad graph and utilizing the NarratorsKG on AR-Sanad 280K-v2 datasetNeural Computing and Applications10.1007/s00521-024-10194-236:36(23169-23180)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s00521-024-10194-2

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