TY - JOUR
T1 - QArabPro
T2 - A rule based question answering system for reading comprehension tests in Arabic
AU - Akour, Mohammed
AU - Abufardeh, Sameer
AU - Magel, Kenneth
AU - Al-Radaideh, Qasem
N1 - Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - 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).
AB - 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).
KW - Acronyms
KW - Arabic Q/A system
KW - Arabic language
KW - Information Extraction (IE)
KW - Information Retrieval (IR)
KW - Morphological analysis
KW - Morphological root
KW - Natural Language Processing (NLP)
KW - QA systems
KW - Stemming-root extraction
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U2 - 10.3844/ajassp.2011.652.661
DO - 10.3844/ajassp.2011.652.661
M3 - Article
AN - SCOPUS:79959431705
SN - 1546-9239
VL - 8
SP - 652
EP - 661
JO - American Journal of Applied Sciences
JF - American Journal of Applied Sciences
IS - 6
ER -