Genetic Algorithms for RFQ Query Path Optimization

Alexander Hogenboom; Viorel Milea; Flavius Frasincar; U Kaymak

Genetic Algorithms for RFQ Query Path Optimization

Alexander Hogenboom, Viorel Milea, Flavius Frasincar, U Kaymak

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

Abstract

In this paper we present an approach based on genetic algorithms for determining optimal RDF query paths. The performance of this approach is benchmarked against the performance of a two-phase optimization algorithm. For more complex queries, the genetic algorithm RDFGA generally outperforms two-phase optimization in solution quality, execution time needed, and consistency in performance. Setting a time limit improves the overall performance of RDFGA compared to two-phase optimization even more.

Original language	Undefined/Unknown
Title of host publication	Proceedings of the First International Workshop on Nature Inspired Reasoning for the Semantic Web
Editors	C. Guéret, P. Hitzler, S. Schlobach
Place of Publication	Karlsruhe, Germany
Pages	16-30
Number of pages	15
Publication status	Published - 27 Oct 2008

Research programs

EUR ESE 32

Cite this

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title = "Genetic Algorithms for RFQ Query Path Optimization",

abstract = "In this paper we present an approach based on genetic algorithms for determining optimal RDF query paths. The performance of this approach is benchmarked against the performance of a two-phase optimization algorithm. For more complex queries, the genetic algorithm RDFGA generally outperforms two-phase optimization in solution quality, execution time needed, and consistency in performance. Setting a time limit improves the overall performance of RDFGA compared to two-phase optimization even more.",

author = "Alexander Hogenboom and Viorel Milea and Flavius Frasincar and U Kaymak",

year = "2008",

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Genetic Algorithms for RFQ Query Path Optimization. / Hogenboom, Alexander; Milea, Viorel; Frasincar, Flavius et al.
Proceedings of the First International Workshop on Nature Inspired Reasoning for the Semantic Web. ed. / C. Guéret; P. Hitzler; S. Schlobach. Karlsruhe, Germany, 2008. p. 16-30.

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

TY - GEN

T1 - Genetic Algorithms for RFQ Query Path Optimization

AU - Hogenboom, Alexander

AU - Milea, Viorel

AU - Frasincar, Flavius

AU - Kaymak, U

PY - 2008/10/27

Y1 - 2008/10/27

N2 - In this paper we present an approach based on genetic algorithms for determining optimal RDF query paths. The performance of this approach is benchmarked against the performance of a two-phase optimization algorithm. For more complex queries, the genetic algorithm RDFGA generally outperforms two-phase optimization in solution quality, execution time needed, and consistency in performance. Setting a time limit improves the overall performance of RDFGA compared to two-phase optimization even more.

AB - In this paper we present an approach based on genetic algorithms for determining optimal RDF query paths. The performance of this approach is benchmarked against the performance of a two-phase optimization algorithm. For more complex queries, the genetic algorithm RDFGA generally outperforms two-phase optimization in solution quality, execution time needed, and consistency in performance. Setting a time limit improves the overall performance of RDFGA compared to two-phase optimization even more.

UR - http://ceur-ws.org/Vol-419/paper3.pdf

M3 - Conference proceeding

SP - 16

EP - 30

BT - Proceedings of the First International Workshop on Nature Inspired Reasoning for the Semantic Web

A2 - Guéret, C.

A2 - Hitzler, P.

A2 - Schlobach, S.

CY - Karlsruhe, Germany

ER -

Genetic Algorithms for RFQ Query Path Optimization

Abstract

Research programs

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