将dag分解为生成树:压缩传递闭包的一种新方法

Yangjun Chen, Yibin Chen
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引用次数: 38

摘要

设G(V, E)是一个有向图(有向图),有n个节点和E条边。有向图G* = (V, E*)是自反的,传递的闭包,如果(V, u)∈E*,如果在G中有一条从V到u的路径,G*的有效存储对于支持可达性查询非常重要,可达性查询不仅在图数据库中很常见,而且是许多图算法中使用的基本操作。人们提出了许多基于图标记的策略,通过给每个节点分配特定的标签,使得任意两个节点通过路径的可达性可以通过它们的标签来确定。其中包括区间标记、链分解和2-hop标记。然而,由于许多现实世界的图非常大,使用现有方法的计算成本和标签的大小将被证明过于昂贵而不实用。在本文中,我们提出了一种新的方法,将图分解为一系列可能共享共同边的生成树,从而将图上的可达性查询转换为树上的查询集。我们从分析和经验两方面证明了我们的方法的效率和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decomposing DAGs into spanning trees: A new way to compress transitive closures
Let G(V, E) be a digraph (directed graph) with n nodes and e edges. Digraph G* = (V, E*) is the reflexive, transitive closure if (v, u) ∈ E* iff there is a path from v to u in G. Efficient storage of G* is important for supporting reachability queries which are not only common on graph databases, but also serve as fundamental operations used in many graph algorithms. A lot of strategies have been suggested based on the graph labeling, by which each node is assigned with certain labels such that the reachability of any two nodes through a path can be determined by their labels. Among them are interval labelling, chain decomposition, and 2-hop labeling. However, due to the very large size of many real world graphs, the computational cost and size of labels using existing methods would prove too expensive to be practical. In this paper, we propose a new approach to decompose a graph into a series of spanning trees which may share common edges, to transform a reachability query over a graph into a set of queries over trees. We demonstrate both analytically and empirically the efficiency and effectiveness of our method.
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