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Ontology-lexicon-based question answering over linked data

  • Jabalameli, Mehdi (Department of Software Engineering, Faculty of Computer Engineering, University of Isfahan) ;
  • Nematbakhsh, Mohammadali (Department of Software Engineering, Faculty of Computer Engineering, University of Isfahan) ;
  • Zaeri, Ahmad (Department of Software Engineering, Faculty of Computer Engineering, University of Isfahan)
  • Received : 2018.06.11
  • Accepted : 2019.07.29
  • Published : 2020.04.03

Abstract

Recently, Linked Open Data has become a large set of knowledge bases. Therefore, the need to query Linked Data using question answering (QA) techniques has attracted the attention of many researchers. A QA system translates natural language questions into structured queries, such as SPARQL queries, to be executed over Linked Data. The two main challenges in such systems are lexical and semantic gaps. A lexical gap refers to the difference between the vocabularies used in an input question and those used in the knowledge base. A semantic gap refers to the difference between expressed information needs and the representation of the knowledge base. In this paper, we present a novel method using an ontology lexicon and dependency parse trees to overcome lexical and semantic gaps. The proposed technique is evaluated on the QALD-5 benchmark and exhibits promising results.

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