Fuzzy Retrieval of Linked Open Data





Publicado en

Actas de las XXII Jornadas sobre Programación y Lenguajes (PROLE 2023)




The technologies associated with the Semantic Web facilitate the publication of Open Data as well as their integration into the Linked Open Data cloud for which RDF format has been chosen. The promoted W3C RDF query language SPARQL became very popular and has been subject of study in recent years, with the goal of improving SPARQL engines in terms of functionality and usability. In this line of research, our research group has developed a fuzzy extension of SPARQL, called FSA-SPARQL (Fuzzy Sets and Aggregators based SPARQL). Here we go a step forward, adapting FSA-SPARQL for querying Linked Open Data with a fuzzy taste. Three goals are pursued, (i) fuzzification of Linked Open Data datasets, (ii) to extend FSA-SPARQL fuzzy aggregation and (iii) to equip FSA-SPARQL with quantification. Fuzzification, that is, interpretation of Linked Open Data datasets as fuzzy sets is made automatically at querying time, using trapezoidal membership functions. Powerful fuzzy aggregation and quantification operators are introduced in FSA-SPARQL based on fuzzy cardinals of fuzzy sets. As a result of the goals, FSA-SPARQL can be used for the retrieval of Linked Open Data datasets in real time, combining fuzzy aggregation and quantification. The proposed extension for FSA-SPARQL has been implemented and the system is available at our Web site.


Acerca de Almendros-Jiménez, Jesus M.

Palabras clave

Semantic Web, Fuzzy Logic, SPARQL, Linked Open Data


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