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Arabic question answering system: a survey

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Abstract

Question answering is a subfield of information retrieval. It is a task of answering a question posted in a natural language. A question answering system (QAS) may be considered a good alternative to search engines that return a set of related documents. The QAS system is composed of three main modules; question analysis, passage retrieval, and answer extraction. Over the years, numerous QASs have been presented for use in different languages. However, the the development of Arabic QASs has been slowed by linguistic challenges and the lack of resources and tools available to researchers. In this survey, we start with the challenges due to the language and how these challenges make the development of new Arabic QAS more difficult. Next, we do a detailed review of several Arabic QASs. This is followed by an in-depth analysis of the techniques and approaches in the three modules of a QAS. We present an overview of important and recent tools that were developed to help the researchers in this field. We also cover the available Arabic and multilingual datasets, and a look at the different measures used to assess QASs. Finally, the survey delves into the future direction of Arabic QAS systems based on the current state-of-the-art techniques developed for question answering in other languages.

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Notes

  1. http://www.cs.man.ac.uk/~ramsay/ArabicTE/.

  2. https://rajpurkar.github.io/SQuAD-explorer/.

  3. https://stackoverflow.com.

  4. https://www.quora.com.

  5. https://uima.apache.org.

  6. http://corpus.quran.com/download/.

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Acknowledgements

This work was funded by the Deanship of Scientific Research at King Saud University through research group no. RG-1441-332, for which the authors are thankful.

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Authors and Affiliations

  1. Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh, 11543, Saudi Arabia

    Tahani H. Alwaneen, Aqil M. Azmi & Hatim A. Aboalsamh

  2. School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore

    Erik Cambria

  3. School of Computing, Edinburgh Napier University, Edinburgh, EH10 5DT, UK

    Amir Hussain

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  1. Tahani H. Alwaneen
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Alwaneen, T.H., Azmi, A.M., Aboalsamh, H.A. et al. Arabic question answering system: a survey. Artif Intell Rev 55, 207–253 (2022). https://doi.org/10.1007/s10462-021-10031-1

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