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• W2006057663 abstract "A data warehouse is designed for answering analytical queries. These queries are usually long, complex and ad hoc in nature and their response time is high when processed against an exponentially growing data warehouse. Materialising views has been found to be an effective tool for reducing this response time. All views cannot be materialised on account of resource constraints. Further, optimal view selection is shown to be an NP-complete problem. This necessitates selection of an appropriate set of views, from amongst all possible views that reduce the query response time. Most of the view selection algorithms are greedy or evolutionary. In this paper, a differential evolution view selection algorithm (DEVSA) that selects the Top-K views from a multi-dimensional lattice is proposed. Further, it is shown that DEVSA when compared to the greedy, genetic and memetic-based view selection algorithms selects comparatively better quality views for higher dimensional datasets." @default.
• W2006057663 created "2016-06-24" @default.
• W2006057663 creator A5005861746 @default.
• W2006057663 creator A5082586952 @default.
• W2006057663 date "2014-01-01" @default.
• W2006057663 modified "2023-10-18" @default.
• W2006057663 title "Materialised view selection using differential evolution" @default.
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• W2006057663 doi "https://doi.org/10.1504/ijica.2014.066499" @default.
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