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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Notes
- 1.
This presentation of RDFS and SPARQL is simplified to fit the needs of this paper.
- 2.
The only case of inconsistency of an RDFS base is related to a type error property for datatype properties. For example, if the age of an individual stated with property \(\texttt {age}\) is an integer, then the triple \(\langle \texttt {juliet}~\texttt {age}~\texttt {true}\rangle \) is inconsistent. Such situations of inconsistencies are not relevant here.
- 3.
These classes are taken from WikiTaaable, the semantic wiki that contains Taaable ontology: http://wikitaaable.loria.fr.
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Bruneau, O., Gaillard, E., Lasolle, N., Lieber, J., Nauer, E., Reynaud, J. (2017). A SPARQL Query Transformation Rule Language — Application to Retrieval and Adaptation in Case-Based Reasoning. In: Aha, D., Lieber, J. (eds) Case-Based Reasoning Research and Development. ICCBR 2017. Lecture Notes in Computer Science(), vol 10339. Springer, Cham. https://doi.org/10.1007/978-3-319-61030-6_6
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