RCQ-GA: RDF Chain Query Optimization using Genetic Algorithms

Alexander Hogenboom, Viorel Milea, Flavius Frasincar, U Kaymak

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

18 Citations (Scopus)


The application of Semantic Web technologies in an Electronic Commerce environment implies a need for good support tools. Fast query engines are needed for efficient querying of large amounts of data, usually represented using RDF. We focus on optimizing a special class of SPARQL queries, the so-called RDF chain queries. For this purpose, we devise a genetic algorithm called RCQ-GA that determines the order in which joins need to be performed for an efficient evaluation of RDF chain queries. The approach is benchmarked against a two-phase optimization algorithm, previously proposed in literature. The more complex a query is, the more RCQ-GA outperforms the benchmark in solution quality, execution time needed, and consistency of solution quality. When the algorithms are constrained by a time limit, the overall performance of RCQ-GA compared to the benchmark further improves.
Original languageEnglish
Title of host publicationTenth International Conference on E-Commerce and Web Technologies
EditorsF. Buccafurri, T. di Noia
Place of PublicationBerlin
Number of pages12
ISBN (Print)9783642039638
Publication statusPublished - 1 Sept 2009

Research programs

  • EUR ESE 32


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