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.
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Chaudhari, M.S., Dhote, C. (2012). Dynamic Materialized View Selection Algorithm: A Clustering Approach. In: Kannan, R., Andres, F. (eds) Data Engineering and Management. ICDEM 2010. Lecture Notes in Computer Science, vol 6411. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27872-3_9
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DOI: https://doi.org/10.1007/978-3-642-27872-3_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27871-6
Online ISBN: 978-3-642-27872-3
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