DAQAS: Deep Arabic Question Answering System based on duplicate question detection and machine reading comprehension Article Swipe
Hamza Alami
,
Abdelkader El Mahdaouy
,
Abdessamad Benlahbib
,
Noureddine En-Nahnahi
,
Ismaïl Berrada
,
Saïd Ouatik El Alaoui
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.jksuci.2023.101709
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.jksuci.2023.101709
As of late, various deep learning techniques and methods have shown their superiority to feature-based and shallow learning techniques in the field of open-domain question–answering systems (OpenQAS). However, only a few works adopted these techniques to build Arabic OpenQAS that can extract exact answers from large information sources (e.g., Wikipedia). In addition, no available Arabic OpenQAS integrated a module to identify duplicate questions to accelerate response time and reduce computation cost. In this paper, we propose an Arabic OpenQAS (named DAQAS) based on deep learning methods. It consists of three components: (1) Dense Duplicate Question Detection which returns answers to questions that already have been answered; (2) Retriever based on BM25 and Query Expansion by neural text generation; and (3) Reader able to extract exact answers given a question and the retrieved passages that probably contains the answer. All components of our system integrate deep learning models, specially transformers-based techniques, which have scored state-of-the-art in different NLP fields. We performed several experiments with publicly available question answering datasets to show the effectiveness of our system. DAQAS obtained promising results and scored 21.77% Exact Match and 54.71% F1 score when using only top 5 retrieved passages.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.jksuci.2023.101709
- OA Status
- hybrid
- Cited By
- 10
- References
- 50
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4385782632
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4385782632Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.jksuci.2023.101709Digital Object Identifier
- Title
-
DAQAS: Deep Arabic Question Answering System based on duplicate question detection and machine reading comprehensionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-08-12Full publication date if available
- Authors
-
Hamza Alami, Abdelkader El Mahdaouy, Abdessamad Benlahbib, Noureddine En-Nahnahi, Ismaïl Berrada, Saïd Ouatik El AlaouiList of authors in order
- Landing page
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https://doi.org/10.1016/j.jksuci.2023.101709Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.jksuci.2023.101709Direct OA link when available
- Concepts
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Question answering, Computer science, Artificial intelligence, Natural language processing, Arabic, Open domain, Deep learning, Transformer, Information retrieval, Computation, Reading (process), Linguistics, Programming language, Philosophy, Quantum mechanics, Physics, VoltageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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10Total citation count in OpenAlex
- Citations by year (recent)
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2025: 5, 2024: 4, 2023: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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