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

Olivier Bruneau 1 Emmanuelle Gaillard 2, 3 Nicolas Lasolle 1 Jean Lieber 3, 2 Emmanuel Nauer 3, 2 Justine Reynaud 2, 3
1 LHSP - Laboratoire d'Histoire des Sciences et de Philosophie - Archives Henri Poincaré
2 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
3 LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
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.
Keywords : adaptation application retrieval query transformation SPARQL RDFS
Type de document :
Communication dans un congrès
ICCBR 2017 - Case-Based Reasoning Research and Development, 25th International Conference on Case-Based Reasoning, Jun 2017, Trondheim, Norway
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Soumis le : mardi 12 décembre 2017 - 09:35:49
Dernière modification le : mardi 12 juin 2018 - 18:18:02

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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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