The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2024.0151224
PDF

A Multimodal Data Scraping Tool for Collecting Authentic Islamic Text Datasets

Author 1: Abdallah Namoun
Author 2: Mohammad Ali Humayun
Author 3: Waqas Nawaz

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 12, 2024.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Making decisions based on accurate knowledge is agreed upon to provide ample opportunities in different walks of life. Machine learning and natural language processing (NLP) systems, such as Large Language Models, may use unrecognized sources of Islamic content to fuel their predictive models, which could often lead to incorrect judgments and rulings. This article presents the development of an automated method with four distinct algorithms for text extraction from static websites, dynamic websites, YouTube videos with transcripts, and for speech-to-text conversion from videos without transcripts, particularly targeting Islamic knowledge text. The tool is tested by collecting a reliable Islamic knowledge dataset from authentic sources in Saudi Arabia. We scraped Islamic content in Arabic from text websites of prominent scholars and YouTube channels administered by five authorized agencies in Saudi Arabia. These agencies include the general authority for the affairs of the grand mosque and the prophet’s mosque and charitable foundations in Saudi Arabia. For websites, text data were scraped using Python tools for static and dynamic web scraping such as Beautiful Soup and Selenium. For YouTube channels, data were scraped from existing transcripts or transcribed using automatic speech recognition tools. The final Islamic content dataset comprises 31225 records from regulated sources. Our Islamic knowledge dataset can be used to develop accurate Islamic question answering, AI chatbots and other NLP systems.

Keywords: Web scraping; Islamic knowledge; machine learning; natural language processing; question and answering; AI chatbots

Abdallah Namoun, Mohammad Ali Humayun and Waqas Nawaz, “A Multimodal Data Scraping Tool for Collecting Authentic Islamic Text Datasets” International Journal of Advanced Computer Science and Applications(IJACSA), 15(12), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151224

@article{Namoun2024,
title = {A Multimodal Data Scraping Tool for Collecting Authentic Islamic Text Datasets},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151224},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151224},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {12},
author = {Abdallah Namoun and Mohammad Ali Humayun and Waqas Nawaz}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org