子集偏序:计算与组合

Amr Elmasry
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引用次数: 5

摘要

给定一个集族F (k),其基数为s1, s2,…,sk, N = [EQUATION],我们证明了由子集关系(称为子集图)引起的偏序图的大小为[EQUATION],其中B = log (N/ log2n)。这意味着对[2]中得出的O(N2/ log2n)界的一个更简单的证明。我们还给出了一种计算任意集合f的子集图的算法。我们的算法在指针机上需要O(nk2/ log k)的时间和空间,其中n是域元素的数量。当F密度较大,即N = Θ(nk)时,算法需要O(N2/ log2n)的时间和空间。我们给出了一个密集族的子集图的大小为Θ(N2/ log2n)的构造,表明了我们的算法对于密集族的最优性。当F在每次更新的O(nk/ log k)时间内进行集的插入和删除时,可以动态维护子集图(对于密集族,这在N中是次线性的)。如果我们假设b个字≤k位,允许以字的形式封装位,并使用按位运算,则上述运行时间和空间需求可以分别减少b log (k/b + 1)/ log k和b2 log (k/b + 1)/ log k。
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The Subset Partial Order: Computing and Combinatorics
Given a family F of k sets with cardinalities s1, s2, . . ., sk and N = [EQUATION], we show that the size of the partial order graph induced by the subset relation (called the subset graph) is [EQUATION], where B = log (N/ log2 N). This implies a simpler proof to the O(N2/ log2 N) bound concluded in [2]. We also give an algorithm that computes the subset graph for any family of sets F. Our algorithm requires O(nk2/ log k) time and space on a pointer machine, where n is the number of domain elements. When F is dense, i.e. N = Θ(nk), the algorithm requires O(N2/ log2 N) time and space. We give a construction for a dense family whose subset graph is of size Θ(N2/ log2 N), indicating the optimality of our algorithm for dense families. The subset graph can be dynamically maintained when F undergoes set insertion and deletion in O(nk/ log k) time per update (that is sub-linear in N for the case of dense families). If we assume words of b ≤ k bits, allow bits to be packed in words, and use bitwise operations, the above running time and space requirements can be reduced by a factor of b log (k/b + 1)/ log k and b2 log (k/b + 1)/ log k respectively.
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