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2022 Volume 37
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A survey on semantic question answering systems

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  • Abstract: Recently, many question answering systems that derive answers from linked data repositories have been developed. The purpose of this survey is to identify the common features and approaches of the semantic question answering (SQA) systems, although many different and prototype systems have been designed. The SQA systems use a formal query language like SPARQL and knowledge of a specific vocabulary. This paper analyses different frameworks, architectures, or systems that perform SQA and classifies SQA systems based on different criteria.
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  • Cite this article

    Christina Antoniou, Nick Bassiliades. 2022. A survey on semantic question answering systems. The Knowledge Engineering Review 37(1), doi: 10.1017/S0269888921000138
    Christina Antoniou, Nick Bassiliades. 2022. A survey on semantic question answering systems. The Knowledge Engineering Review 37(1), doi: 10.1017/S0269888921000138
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REVIEW   Open Access    

A survey on semantic question answering systems

  • Received: 11 December 2020
  • Revised: 25 October 2021
  • Accepted: 27 October 2021
  • Published online: 20 January 2022
The Knowledge Engineering Review  37,  2022, 37(1)  |  Cite this article

Abstract: Abstract: Recently, many question answering systems that derive answers from linked data repositories have been developed. The purpose of this survey is to identify the common features and approaches of the semantic question answering (SQA) systems, although many different and prototype systems have been designed. The SQA systems use a formal query language like SPARQL and knowledge of a specific vocabulary. This paper analyses different frameworks, architectures, or systems that perform SQA and classifies SQA systems based on different criteria.

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    Christina Antoniou, Nick Bassiliades. 2022. A survey on semantic question answering systems. The Knowledge Engineering Review 37(1), doi: 10.1017/S0269888921000138
    Christina Antoniou, Nick Bassiliades. 2022. A survey on semantic question answering systems. The Knowledge Engineering Review 37(1), doi: 10.1017/S0269888921000138
    shu

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