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ALPS: an efficient algorithm for top-k spatial preference search in road networks

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Abstract

In this paper, we study the processing of top-k spatial preference queries in road networks. A top-k spatial preference query retrieves a ranked list of the k best data objects based on the scores (e.g., qualities) of feature objects in their spatial neighborhoods. Several solutions have been proposed for top-k spatial preference queries in Euclidean space. However, far too little attention has been paid to top-k spatial preference queries in road networks, where the distance between two points is defined by the length of the shortest path connecting them. A simple way to answer top-k spatial preference queries is to examine the scores of feature objects in the proximity of each data object before returning a ranked list of the k best data objects. However, this simple method causes intolerable computation delays, thus rendering online processing inapplicable. Therefore, in this paper, we address this problem by presenting a new algorithm, called ALPS, for top-k spatial preference searches in road networks. Our experimental results demonstrate the superiority and effectiveness of ALPS for a wide range of problem settings.

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Acknowledgments

We thank the anonymous reviewers for their very useful comments and suggestions. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2012R1A1A2043422).

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  1. Department of Information and Computer Engineering, Ajou University, Suwon-si, Gyeonggi-do, South Korea

    Hyung-Ju Cho, Se Jin Kwon & Tae-Sun Chung

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  1. Hyung-Ju Cho
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  2. Se Jin Kwon
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  3. Tae-Sun Chung
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Correspondence to Hyung-Ju Cho.

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Cho, HJ., Kwon, S.J. & Chung, TS. ALPS: an efficient algorithm for top-k spatial preference search in road networks. Knowl Inf Syst 42, 599–631 (2015). https://doi.org/10.1007/s10115-013-0696-9

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