A Novel Approach for Generating SPARQL Queries from RDF Graphs
–arXiv.org Artificial Intelligence
This work is done as part of a research master's thesis project. The goal is to generate SPARQL queries based on user-supplied keywords to query RDF graphs. To do this, we first transformed the input ontology into an RDF graph that reflects the semantics represented in the ontology. Subsequently, we stored this RDF graph in the Neo4j graphical database to ensure efficient and persistent management of RDF data. At the time of the interrogation, we studied the different possible and desired interpretations of the request originally made by the user. We have also proposed to carry out a sort of transformation between the two query languages SPARQL and Cypher, which is specific to Neo4j. This allows us to implement the architecture of our system over a wide variety of BD-RDFs providing their query languages, without changing any of the other components of the system. Finally, we tested and evaluated our tool using different test bases, and it turned out that our tool is comprehensive, effective, and powerful enough.
arXiv.org Artificial Intelligence
May-30-2020
- Country:
- Africa > Middle East
- Morocco > Casablanca-Settat Region
- Casablanca (0.04)
- Tunisia
- Jendouba Governorate > Jendouba (0.04)
- Tunis Governorate > Tunis (0.04)
- Morocco > Casablanca-Settat Region
- Asia (0.04)
- Europe > France
- Pays de la Loire > Loire-Atlantique > Nantes (0.04)
- Africa > Middle East
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- Research Report (0.49)
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