Abstract
Location recommendation is essential for various map-based mobile applications. However, it is not easy to generate location-based recommendations with the changing contexts and locations of mobile users. Skyline operation is one of the most well-established techniques for location-based services. Our previous work proposed a new query method, called “area skyline query”, to select areas in a map. However, it is not efficient for large-scale data. In this paper, we propose a parallel algorithm for processing the area skyline using MapReduce. Intensive experiments on both synthetic and real data confirm that our proposed algorithm is sufficiently efficient for large-scale data.
Subject
Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science
Reference21 articles.
1. Area skyline query for selecting good locations in a map;Zaman;J. Inf. Process,2016
Cited by
6 articles.
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