MapReduce Algorithm for Location Recommendation by Using Area Skyline Query
MapReduce Algorithm for Location Recommendation by Using Area Skyline Query
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DOI：
10.3390/a11120191
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发表时间：
2018-11
期刊：
影响因子：
2.3
通讯作者：
Chen Li-;Annisa;Asif Zaman;Mahboob Qaosar;Saleh Ahmed;Y. Morimoto
中科院分区：
文献类型：
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作者：
Chen Li-;Annisa;Asif Zaman;Mahboob Qaosar;Saleh Ahmed;Y. Morimoto
位置推荐对于各种基于地图的移动的应用是必不可少的。然而，这是不容易的，以产生基于位置的建议与不断变化的上下文和位置的移动的用户。Skyline操作是用于基于位置的服务的最完善的技术之一。我们的前期工作提出了一种新的查询方法，称为“区域天际线查询”，以选择在地图中的区域。但是，它对于大规模数据并不有效。在本文中，我们提出了一个并行算法处理的面积天际线使用MapReduce。在合成数据和真实的数据上的大量实验证实了我们提出的算法对于大规模数据是足够有效的。
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.