Genetic algorithms for RFQ query path optimization

A.C. Hogenboom; D.V. Milea; F. Frasincar; U. Kaymak

Genetic algorithms for RFQ query path optimization

A.C. Hogenboom, D.V. Milea, F. Frasincar, U. Kaymak

Information Systems IE&IS

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › 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	English
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
Publication status	Published - 2008

Cite this

@inproceedings{c4eadb7ca9d34db0a0aabe9a9d08afa9,

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 = "A.C. Hogenboom and D.V. Milea and F. Frasincar and U. Kaymak",

year = "2008",

language = "English",

pages = "16--30",

editor = "C. Gu{\'e}ret and P. Hitzler and S. Schlobach",

booktitle = "Proceedings of the First International Workshop on Nature Inspired Reasoning for the Semantic Web",

}

Genetic algorithms for RFQ query path optimization. / Hogenboom, A.C.; Milea, D.V.; Frasincar, F. 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 in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Genetic algorithms for RFQ query path optimization

AU - Hogenboom, A.C.

AU - Milea, D.V.

AU - Frasincar, F.

AU - Kaymak, U.

PY - 2008

Y1 - 2008

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.

M3 - Conference contribution

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

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