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Pré-Publication, Document De Travail Année : 2022

NLDS-QL: From natural language data science questions to queries on graphs: analysing patients conditions & treatments

Genoveva Vargas-Solar
Karim Dao
  • Fonction : Auteur
Mirian Halfeld Ferrari Alves
  • Fonction : Auteur

Résumé

This paper introduces NLDS-QL, a translator of data science questions expressed in natural language (NL) into data science queries on graph databases. Our translator is based on a simplified NL described by a grammar that specifies sentences combining keywords to refer to operations on graphs with the vocabulary of the graph schema. The demonstration proposed in this paper shows NLDS-QL in action within a scenario to explore and analyse a graph base on patient diagnoses generated with the open-source Synthea.

Dates et versions

hal-03758659 , version 1 (23-08-2022)

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Citer

Genoveva Vargas-Solar, Karim Dao, Mirian Halfeld Ferrari Alves. NLDS-QL: From natural language data science questions to queries on graphs: analysing patients conditions & treatments. 2022. ⟨hal-03758659⟩
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