Title: A genetic approach for materialised skyline views selection problem

Authors: Samiha Brahimi; Mohamed-Khireddine Kholladi

Addresses: MISC Laboratory, University of Constantine 2, Algeria ' MISC Laboratory, University of L'Oued, Algeria

Abstract: The materialisation of views has been one of the most successful techniques in optimising OLAP queries. In this context, many works have been conducted aiming either at studying the relationships between the views or at solving the materialised views selection problem. For skyline queries, researchers investigated only the first phase of the materialisation whereas the second phase which is the materialised skyline views selection problem has never been studied because of the difficulty of creating a cost model. In this paper, we propose a genetic method for the materialised skyline views selection problem. In order to reduce the high cost produced by evaluating the skycube all over the selection process, we propose a time reducing heuristic called OnceVisited which avoids the computation of the same query from the same views many times. The conducted experiments have proven the efficiency of the genetic approach since high quality solutions have been found. In addition, the proposed time reducing heuristic OnceVisited has been shown to be very efficient.

Keywords: skyline queries; skycube; materialisation of views; cost reducing; genetic algorithms; data mining; Orion; Top-Sky; view selection; OLAP queries.

DOI: 10.1504/IJDMMM.2016.079060

International Journal of Data Mining, Modelling and Management, 2016 Vol.8 No.3, pp.223 - 243

Received: 29 Aug 2014
Accepted: 04 Dec 2014

Published online: 12 Sep 2016 *

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