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Sabry, N., Sauber, A., El-Kafrawy, P. (2022). Surveying Question Answering Systems: A Comparative Study. The Egyptian Journal of Language Engineering, 9(1), 22-31. doi: 10.21608/ejle.2022.118590.1029
Nada Sabry; Amr Sauber; Passant El-Kafrawy. "Surveying Question Answering Systems: A Comparative Study". The Egyptian Journal of Language Engineering, 9, 1, 2022, 22-31. doi: 10.21608/ejle.2022.118590.1029
Sabry, N., Sauber, A., El-Kafrawy, P. (2022). 'Surveying Question Answering Systems: A Comparative Study', The Egyptian Journal of Language Engineering, 9(1), pp. 22-31. doi: 10.21608/ejle.2022.118590.1029
Sabry, N., Sauber, A., El-Kafrawy, P. Surveying Question Answering Systems: A Comparative Study. The Egyptian Journal of Language Engineering, 2022; 9(1): 22-31. doi: 10.21608/ejle.2022.118590.1029

Surveying Question Answering Systems: A Comparative Study

Article 3, Volume 9, Issue 1, April 2022, Page 22-31  XML PDF (1.2 MB)
Document Type: Original Article
DOI: 10.21608/ejle.2022.118590.1029
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Authors
Nada Sabry email 1; Amr Sauberorcid 2; Passant El-Kafrawy3
1Department of Physics and Computer science, Faculty of science, Menofia university, Menofia, Menouf
2Department of Mathematics and Computer Science, Faculty of Science, Menoufia University
3School of Information Technology and Computer Science, Nile University, Giza 12588, Egypt
Abstract
Question Answering (QA) systems are considered an advanced form of information retrieval that enables asking specific questions by humans and the system infer answers using natural language queries with deeper knowledge understanding mechanisms from huge amount of data instead of having the user search all documents himself. As what a user really wants is often a precise answer to a question by consulting documents on the web or using special knowledge base.
Although many systems have been developed over the past years, it remains a challenge that most systems yet require improvements to increase the accuracy for correct interpretation of the question and provide a good exact answer to user questions. This paper presents a short study of the generic QA framework and aims to survey some of the current state-of-the-art Question Answering systems in different domains and makes a comparison between all of these systems based on some identified criteria in literature.
Keywords
Question Answering Systems; Natural Language Processing; Information Retrieval; Knowledge Representation
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