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Skyline Nearest Neighbor Search on Multi-layer Graphs

机译:在多层图表上的天际线最近邻居搜索

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Nearest neighbor search is a fundamental problem in graph theory. In real-world applications, the multi-layer graph model is extensively studied to reveal the multi-dimensional relations between the graph entities. In this paper, we formulate a new problem named skyline nearest neighbor search on multi-layer graphs. Given a query vertex u, we aim to compute a set of skyline vertices that are not dominated by other vertices in terms of the shortest distance on all graph layers. We propose an early-termination algorithm instead of naively adopting the traditional skyline procedure as a subroutine. We also investigate the rule to optimize search order in the algorithm and further improve the algorithmic efficiency. The experimental results demonstrate that the optimization strategies work well on different graphs and can speed up the algorithm significantly.
机译:最近的邻居搜索是图论中的一个根本问题。在现实世界应用中,广泛研究多层图模型,以揭示图形实体之间的多维关系。在本文中,我们在多层图中制定了名为Skyline最近邻搜索的新问题。给定查询顶点u,我们的目标是在所有图形图层上的最短距离方面计算一组不受其他顶点的地平线顶点。我们提出了一种早期终止算法,而不是天鹅地采用传统的天际线手术作为子程序。我们还调查规则以优化算法中的搜索顺序,进一步提高算法效率。实验结果表明,优化策略在不同的图表上运作良好,并且可以显着加速算法。

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