Genetic Algorithms for RDF Chain Query Optimization

Alexander Hogenboom, Viorel Milea, Flavius Frasincar, U Kaymak

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review


The application of Semantic Web technologies in an Electronic Commerce environment implies a need for good support tools. Fast query engines are required for efficient real-time querying of large amounts of data, usually represented using RDF. We focus on optimizing a special class of SPARQL queries: RDF chain queries. We devise a genetic algorithm, 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 improves even further.
Original languageEnglish
Title of host publicationProceedings of the Twenty-First Benelux Conference on Artificial Intelligence
EditorsT. Calders, K. Tuyls, M. Pechenizkiy
Place of PublicationEindhoven, The Netherlands
Number of pages2
Publication statusPublished - 29 Oct 2009


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