Abstract
The Resource Description Framework (RDF) is the W3C recommended standard for data on the semantic web, while the SPARQL Protocol and RDF Query Language (SPARQL) is the query language that retrieves RDF triples. RDF data often contain valuable information that can only be queried through filter functions. The SPARQL query language for RDF can include filter clauses in order to define specific data criteria, such as full-text searches, numerical filtering, and constraints and relationships between data resources. However, the downside of executing SPARQL filter queries is the frequently slow query execution times. This paper presents a SPARQL filter query-processing engine for conventional triplestores called FILT (Filtering Indexed Lucene Triples), built on top of the Apache Lucene framework for storing and retrieving indexed documents, compatible with unmodified SPARQL queries. The objective of FILT was to decrease the query execution time of SPARQL filter queries. This aspect was evaluated by performing a benchmark test of FILT compared to the Joseki triplestore, focusing on two different use-cases; SPARQL regular expression filtering in medical data, and SPARQL numerical/logical filtering of geo-coordinates in geographical locations.
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Stuhr, M., Veres, C. (2013). FILT – Filtering Indexed Lucene Triples – A SPARQL Filter Query Processing Engine–. In: Larsen, H.L., Martin-Bautista, M.J., Vila, M.A., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2013. Lecture Notes in Computer Science(), vol 8132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40769-7_3
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DOI: https://doi.org/10.1007/978-3-642-40769-7_3
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