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Sorting and Selection in Posets

机译:在POSETS中排序和选择

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Classical problems of sorting and searching assume an underlying linear ordering of the objects being compared. In this paper, we study these problems in the context of partially ordered sets, in which some pairs of objects are incomparable. This generalization is interesting from a combinatorial perspective, and it has immediate applications in ranking scenarios where there is no underlying linear ordering, e.g., conference submissions. It also has applications in reconstructing certain types of networks, including biological networks. Our results represent significant progress over previous results from two decades ago by Faigle and Turan. In particular, we present the first algorithm that sorts a width-w poset of size n with optimal query complexity O(n(w + logn)). We also describe a variant of Merge-sort with query complexity O(wn log (n/w)) and total complexity O(w~2n log (n/w)); an algorithm with the same query complexity was given by Faigle and Turan, but no efficient implementation of that algorithm is known. Both our sorting algorithms can be applied with negligible overhead to the more general problem of reconstructing transitive relations. We also consider two related problems: finding the minimal elements, and its generalization to finding the bottom k "levels", called the k-selection problem. We give efficient deterministic and randomized algorithms for finding the minimal elements with O(wn) query and total complexity. We provide matching lower bounds for the query complexity up to a factor of 2 and generalize the results to the k-selection problem. Finally, we present efficient algorithms for computing a linear extension of a poset and computing the heights of all elements.
机译:排序和搜索的经典问题假设进行比较对象的底层线性排序。在本文中,我们在部分有序集的上下文中研究了这些问题,其中一些对象是无与伦比的。这种概括是从组合角度的有趣,它在排名方案中具有直接应用程序,其中没有底层线性排序,例如,会议提交。它还具有重建某些类型的网络的应用,包括生物网络。我们的结果代表了Faigle和Turan二十年前以前对以往的结果的重大进展。特别是,我们介绍了具有最佳查询复杂度O的大小N的宽度-W Poset的第一算法(n(w + logn))。我们还描述了具有查询复杂性O的合并 - 排序的变体(WN Log(N / W))和总复杂性O(W〜2N日志(N / W)); Faigle和Turan给出了具有相同查询复杂性的算法,但没有有效地实现该算法。我们的排序算法都可以应用于重建及物关系的更一般性问题。我们还考虑了两个相关问题:找到最小的元素,以及找到底部k“级别”的概率,称为k选择问题。我们提供有效的确定性和随机化算法,用于查找具有O(WN)查询和总复杂性的最小元素。我们提供匹配的下限,用于查询复杂性高达2倍,并将结果概括为k选择问题。最后,我们提出了用于计算POSET的线性扩展和计算所有元素的高度的高效算法。

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