Abstract
A data warehouse can be seen as a set of materialized views defined over remote base relation. When the query is posed, it is evaluated locally using the materialized view without accessing the original database. The paper proposes clustering based dynamic materialized view selection algorithm. The base of the paper is to propose similarity function, clustering materialized view and then dynamically adjusting the materialized view. © 2012 Springer-Verlag.
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CITATION STYLE
Chaudhari, M. S., & Dhote, C. (2012). Dynamic materialized view selection algorithm: A clustering approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6411 LNCS, pp. 57–66). https://doi.org/10.1007/978-3-642-27872-3_9
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