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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 5, 2019.
Abstract: A skyline query finds objects that are not dominated by another object from a given set of objects. Skyline queries help us to filter unnecessary information efficiently and provide us clues for various decision making tasks. In this paper, we consider skyline queries for location-based services and proposed a framework that can efficiently compute all non-dominated paths in road networks. A path p is said to dominate another path q if p is not worse than q in any of the k dimensions and p is better than q in at least one of the k dimensions. Our proposed skyline framework considers several features related to road networks and return all non-dominated paths from the road networks. In our work, we compute skylines considering two different perspectives: business perspective and individual user’s perspective. We have conducted several experiments to show the effectiveness of our method. From the experimental results, we can say that our system can perform efficient computation of skyline paths from road networks.
Nishu Chowdhury and Mohammad Shamsul Arefin, “Skyline Path Queries for Location-based Services” International Journal of Advanced Computer Science and Applications(IJACSA), 10(5), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100555
@article{Chowdhury2019,
title = {Skyline Path Queries for Location-based Services},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100555},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100555},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {5},
author = {Nishu Chowdhury and Mohammad Shamsul Arefin}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.