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Reducing computational complexity of skyline by the use of logical and physical bucket
P GHOSH, L J GHOSH, S GUHA, N C DEBNATH,
Published in Springer Verlag
2019
Volume: 812
   
Pages: 123 - 131
Abstract
Multi-criteria decision making problem when applied on relational model multiple attributes of tables are analyzed. In this context, the system has to be capable of identifying non-dominated tuples (points). One of the common solutions is runtime computation of skyline. Points those are not dominated by any other point in the system are called Skyline point. Hence computation is required to search non-dominated tuples (points) of the system. Traditional skyline computations require observations of each point and compare to all the other points in the system which incurs high time complexity. Moreover skyline demands the attributes to have complementary relationship. In this paper an alternative approach is proposed to use the features of skyline but avoiding the constraints of skyline. The proposed methodology categorizes the attributes in three classes and calculates the cost associated with each dimension in a sequence to reduce complexity. © Springer Nature Singapore Pte Ltd. 2019.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer Verlag
ISSN2194-5357
Open AccessNo