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Conference Papers Year : 2017

A SPARQL Query Transformation Rule Language — Application to Retrieval and Adaptation in Case-Based Reasoning

Abstract

This paper presents SQTRL, a language for transformation rules for SPARQL queries, a tool associated with it, and how it can be applied to retrieval and adaptation in case-based reasoning (CBR). Three applications of SQTRL are presented in the domains of cooking and digital humanities. For a CBR system using RDFS for representing cases and domain knowledge, and SPARQL for its query language, case retrieval with SQTRL consists in a minimal modification of the query so that it matches at least a source case. Adaptation based on the modification of an RDFS base can also be handled with the help of this tool. SQTRL and its tool can therefore be used for several goals related to CBR systems based on the semantic web standards RDFS and SPARQL.
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Dates and versions

hal-01661651 , version 1 (12-12-2017)

Identifiers

  • HAL Id : hal-01661651 , version 1

Cite

Olivier Bruneau, Emmanuelle Gaillard, Nicolas Lasolle, Jean Lieber, Emmanuel Nauer, et al.. A SPARQL Query Transformation Rule Language — Application to Retrieval and Adaptation in Case-Based Reasoning. ICCBR 2017 - Case-Based Reasoning Research and Development, 25th International Conference on Case-Based Reasoning, Jun 2017, Trondheim, Norway. ⟨hal-01661651⟩
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