ARmed question answering system

Summary Question answering, retrieving an exact answer to a question posed in natural language, is an issue which has widely been studied in the open domain over the last decades. This, however, remains a real challenge in the medical domain as most existing systems only support a limited amount of...

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Bibliographic Details
Published in:Concurrency and computation 2022-09, Vol.34 (21), p.n/a
Main Authors: Fehri, Hela, Dardour, Sondes, Haddar, Kais
Format: Article
Language:English
Subjects:
Arabic language
disambiguation
Domains
information retrieval
natural language processing
question answering
Questions
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Summary:Summary Question answering, retrieving an exact answer to a question posed in natural language, is an issue which has widely been studied in the open domain over the last decades. This, however, remains a real challenge in the medical domain as most existing systems only support a limited amount of question and answer types. The problem with proposed methods for Arabic language in the medical domain is that there is often a conflict between the extracted answer and user's requirements. This conflict is related to ambiguity. Nevertheless, the method we propose has successfully tackled this problem. Thus, in this article, we introduce ARmed, a system for automatically answering medical questions for Arabic language. ARmed consists of corpora study, pre‐processing, question analysis, documents/passages retrieval, and answer extraction. Compared with the previous studies, ARmed has the potential to handle a large number of questions and answer types. The experimental results show that ARmed achieves interesting results.
ISSN:1532-0626
1532-0634
DOI:10.1002/cpe.7054