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Top- k Competitive Location Selection over Moving Objects

机译:顶部 - <斜体> k 竞争位置选择移动物体

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The location selection (LS) problem identifies an optimal site to place a new facility such that its influence on given objects can be maximized. With the proliferation of GPS-enabled mobile devices, LS studies have made progress for moving objects. However, the state-of-the-art LS techniques over moving objects assume the new facility has no competitor, which is too restrictive and unrealistic for real-world business. In this paper we study Competitive Location Selection over Moving objects (CLS-M), which takes into account competition against existing facilities in mobile scenarios. We present a competition-based influence score model to evaluate the influence of a candidate. To solve the problem, we propose an influence pruning algorithm to prune objects who are either influenced by inferior candidates or affected by no candidate. Experimental study over two real-world datasets demonstrates that the proposed algorithm outperforms state-of-the-art LS techniques in terms of efficiency.
机译:位置选择(LS)问题标识到放置新设施的最佳站点,使其对给定对象的影响可以最大化。随着支持GPS的移动设备的扩散,LS研究已经为移动物体进行了进展。然而,在移动物体上的最先进的LS技术假设新设施没有竞争对手,这对于真实世界的业务来说太限制性和不切实际。在本文中,我们研究了竞争位置选择对移动物体(CLS-M),这考虑到移动方案中现有设施的竞争。我们提出了一种基于竞争的影响分数模型,以评估候选人的影响。为了解决这个问题,我们提出了影响修剪算法,以修剪受候选者或未受到候选人影响的影响。两个真实数据集的实验研究表明,所提出的算法在效率方面优于最先进的LS技术。

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