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Whale optimization algorithm for solving association rule mining issue

Show simple item record Heraguemi, KamelEddine Kadri, Houria Zabi, Amira 2020-07-21T11:38:23Z 2020-07-21T11:38:23Z 2021-02-08
dc.identifier.issn 2210-142X
dc.description.abstract Our-days, with the significant number of connected devices, data stored has grown significantly. The exploitation of the information stored in it for decision-making has become indispensable in the most prominent companies. Association rule mining draws in consideration of researchers to extract relationships between items in data. Nevertheless, this process is costly in terms of memory and computation, Which are the foremost drawbacks in exact algorithms designed for mining association rule. Recently, swarm-based algorithms prove their efficiency in data mining. With this in mind, an updated whale optimization algorithm to mine association rules, called (WO-ARM), proposed in this paper. Whale optimization has a good trade-off between intensification and diversification, which inherited by our proposal. A set of tests carried out on different famous benchmarks. The preliminary results show that our approach beats other swarm inspired algorithms already exist in the literature in terms of quality, runtime, and memory usage. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri *
dc.subject Association rule mining, Whale optimization algorithm, Support,, Confidence, swarm inspired algorithm en_US
dc.title Whale optimization algorithm for solving association rule mining issue en_US
dc.volume 10 en_US
dc.issue 1
dc.pagestart 333 en_US
dc.pageend 342 en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US

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