@article {10.3844/ajassp.2011.652.661,
article_type = {journal},
title = {QArabPro: A Rule Based Question Answering System for Reading Comprehension Tests in Arabic},
author = {Akour, Mohammed and Abufardeh, Sameer and Magel, Kenneth and Al-Radaideh, Qasem},
volume = {8},
year = {2011},
month = {Jun},
pages = {652-661},
doi = {10.3844/ajassp.2011.652.661},
url = {https://thescipub.com/abstract/ajassp.2011.652.661},
abstract = {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 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 questionanswering
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).},
journal = {American Journal of Applied Sciences},
publisher = {Science Publications}
}