Abstract
Effective analysis of genome sequences and associated functional data requires access to many different kinds of biological information. A data warehouse [14,16] plays an important role for storage and analysis for genome sequence and functional data. A data warehouse stores lots of materialized views to provide an efficient decision-support or OLAP queries. The view-selection problem addresses to select a fittest set of materialized views from a variety of MVPPs 0 forms a challenge in data warehouse research. In this paper, we present genetic algorithm to choose materialized views. We also use experiments to demonstrate the power of our approach.
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We would like to thank the authors, i.e. J. Yang, K. Karlapalem, and Q. Li, of the paper [15]. In this study, we borrow their mathematical model of the work in [15].
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Horng, JT., Chang, YJ. & Liu, BJ. Applying evolutionary algorithms to materialized view selection in a data warehouse. Soft Computing 7, 574–581 (2003). https://doi.org/10.1007/s00500-002-0243-1
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DOI: https://doi.org/10.1007/s00500-002-0243-1