QArabPro: A rule based question answering system for reading comprehension tests in Arabic

Mohammed Akour, Sameer Abufardeh, Kenneth Magel, Qasem Al-Radaideh

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


Problem statement: Extensive research efforts in the area of Natural Language Processing (NLP) were focused on developing reading comprehension Question Answering systems (QA) for Latin based languages such as, English, French and German. Approach:However, little effort was directed towards the development of such systems for bidirectional languages such as Arabic, Urdu and Farsi. In general, QA systems are more sophisticated and more complex than Search Engines (SE) because they seek a specific and somewhat exact answer to the query. Results: Existing Arabic QA system including the most recent described in (Hammo and Kanaan et al.,) excluded one or both types of questions (How and Why) from their work because of the difficulty of handling these questions. In this study, we present a new approach and a new question-answering system (QArabPro) for reading comprehension texts in Arabic. The overall accuracy of our system is 84%. Conclusion/Recommendations: These results are promising compared to existing systems. Our system handles all types of questions including (How and why).

Original languageEnglish (US)
Pages (from-to)652-661
Number of pages10
JournalAmerican Journal of Applied Sciences
Issue number6
StatePublished - 2011
Externally publishedYes


  • Acronyms
  • Arabic Q/A system
  • Arabic language
  • Information Extraction (IE)
  • Information Retrieval (IR)
  • Morphological analysis
  • Morphological root
  • Natural Language Processing (NLP)
  • QA systems
  • Stemming-root extraction


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