Cited by 4Topic ModelingNatural Language Processing TechniquesExpert finding and Q&A systems

The DOI matches its Crossref record.

An English Islamic Articles Dataset (EIAD) for developing an IslamBot Question Answering Chatbot

Mohammed, Moataz, Amin, Salsabil, Aref, Mostafa M.·2022·2022 5th International Conference on Computing and Informatics (ICCI)

Abstract

A chatbot is one of the most vastly recommended technologies to be used during these decades, especially through the digitization era. It could save much consumed time for both the users and the customer service employees. Chatbots could provide an answer to the asked questions instantly. IslamBot is an Islamic religion chatbot “i.e.,” responsible for answering any inquiries related to the Islamic religion. The aimed audience is non-Muslims people willing to join Islam or New-Muslims. Building such types of chatbots need to have an enormous amount of trusted data. Accordingly, in this paper The English Islamic Articles dataset (EIAD) is proposed as a benchmark reference for English Islamic question answering. So, this dataset contains about 10000 English Islamic articles. It is scrapped from authenticated and trusted websites like NewMuslims.com [1] IslamReligion.com [2], and IslamQA.com [3]. The dataset is about 275 articles from NewMuslims.com [1], 1550 articles from IslamReligion.com [2], and 8292 articles from IslamQA.com [3]. The EIAD dataset is a structured dataset “i.e.,” labeled and categorized. This dataset contains about 15 different categories. Each category is covering several different topics. This paper focuses on discussing how The English Islamic Articles dataset (EIAD) has been collected.

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Crossref · 10.1109/icci54321.2022.9756122

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Research works printed but not linked: 17

  1. 0, binbaz org sa/articles
  2. 0, Arabic AskFM dataset - Omar Essam
  3. 0, www alifta gov sa
  4. 0, AlFawzan af org sa
  5. 0, The Holy Quran I Kaggle
  6. 0, Database 2012–2020 on anti-Muslim hatred - Data Europa EU
  7. 0, Google Colaboratory Lab
  8. 0, BeautifulSoup Package
  9. corney, 2016, What do a Million News Articles Look like?
  10. 0, Categories - Islam Question & Answer
  11. corney, 0, What do a Million News Articles Look like?, NewsIR ECIR
  12. 10.1145/1143844.1143892 · DOI
  13. 0, fatwapedia com
  14. 10.47760/ijcsmc.2021.v10i04.017 · DOI
  15. 0, Islam Religion Website
  16. 0, website of New Muslims
  17. 0, binothaimeen net

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Metadata

Authors
Mohammed, M., Amin, S., & Aref, M. M.
Affiliations
  • Ain Shams University (EG)
  • Ain Shams University,Faculty of Computer and Information Sciences,Basic Science Department,Cairo,Egypt
Venue
2022 5th International Conference on Computing and Informatics (ICCI)
Publisher
IEEE
Published
2022-03-09
Pages
303-309
OpenAlex
W4224274657
Cited by
4
References
0
Citations by year
2024: 1 · 2023: 3
FWCI
0.55
Type
conference paper
Language
en
Open access
closed
Locations
International Conference on Computing and Informatics (ICCI) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
  • Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
  • Physical Sciences › Computer Science › Information Systems › Expert finding and Q&A systems
Keywords
chatbots, datasets, benchmark, new Muslims, web scraping, question answering

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