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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

Materialized View Selection Using Backtracking Search Optimization Algorithm

verfasst von : Anjana Gosain, Kavita Sachdeva

Erschienen in: Intelligent Engineering Informatics

Verlag: Springer Singapore

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Abstract

Selecting the materialized views optimally is very important in designing a data warehouse and is NP-hard problem. Various evolutionary algorithms exist in literature for the appropriate selection of materialized views. In this paper, we have examined the application of backtracking search optimization algorithm (BSA), for selecting the materialized views in data warehouse. According to our experiments, the results obtained by our proposed backtracking search optimization-based materialized view selection algorithm (BSMVSA) are superior to those found using particle swarm optimization and genetic algorithm. The solution obtained by BSMVSA greatly reduces the total cost within the storage constraint.

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Metadaten
Titel
Materialized View Selection Using Backtracking Search Optimization Algorithm
verfasst von
Anjana Gosain
Kavita Sachdeva
Copyright-Jahr
2018
Verlag
Springer Singapore
Buch
Intelligent Engineering Informatics

Print ISBN: 978-981-10-7565-0

Electronic ISBN: 978-981-10-7566-7

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-981-10-7566-7_25