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An Even Faster and More Unifying Algorithm for Comparing Trees via Unbalanced Bipartite Matchings

机译:通过不平衡二分匹配对树木进行比较的更快,更统一的算法

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A widely used method for determining the similarity of two labeled trees is to compute a maximum agreement subtree of the two trees. Previous work on this similarity measure has only been concerned with the comparison of labeled trees of two special kinds, namely, uniformly labeled trees (i.e., trees with all their nodes labeled will the same symbol) and evolutionary trees (i.e., leaf-labeled trees with distinct symbols for distinct leaves). This paper presents an algorithm for comparing trees that are labeled in an arbitrary manner. In addition to this generality, this algorithm is faster than the previous algorithms. Another contribution of this paper is on maximum weight bipartite matchings. We show how to speed up the best known matching algorithms when the input graphs are node-unbalanced or weight-unbalanced. Based on these enhancements, we obtain an efficient algorithm for a new matching problem called the hierarchical bipartite matching problem, which is at the core of our maximum agreement subtree algorithm.
机译:确定两个标记树的相似性的一种广泛使用的方法是计算两个树的最大一致性子树。以前关于这种相似性度量的工作仅涉及比较两种特殊类型的标记树,即,统一标记的树(即,所有节点标记为相同符号的树)和进化树(即,叶标记的树)的比较。带有用于不同叶子的不同符号)。本文提出了一种用于比较以任意方式标记的树的算法。除了这种通用性之外,该算法比以前的算法要快。本文的另一个贡献是最大权重二分匹配。我们展示了当输入图是节点不平衡或权重不平衡时,如何加快最著名的匹配算法。基于这些增强,我们获得了一种有效的算法,用于解决新的匹配问题,称为分层二分匹配问题,这是我们最大一致性子树算法的核心。

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