In this paper we study the expected running time of a variety of algorithms that perform set merging. The set merging problem (for example, see AHU [1]) is concerned with using suitable data structures to represent partition of a set S &equil; { 1,2, .... ,n} so that a sequence of instructions of the form "x &Xgr; y", meaning
"Find the subset containing x; Find the subset containing y; Merge the two subsets if they are different."
may be carried out efficiently. Several alternative data structures for solving this problem are known, and their worse-case complexity fairly well understood [3], [4], [5], [8]. In contrast, the average behavior of even the most basic of these schemes remains an open problem [6]. It is the purpose of the present paper to determine the average behavior for several of the set merging algorithms commonly known.
在本文中,我们研究了执行集合合并的各种算法的预期运行时间。集合合并问题(例如,参见AHU [1])与使用合适的数据结构表示集合S&equil;的分区有关。 {1,2,....,n},因此一系列指令的形式为“ x&Xgr; y”,含义 P>
“查找包含x的子集;查找包含y的子集;如果两个子集不同,则将其合并。” P>
可以有效地执行。已知有几种解决此问题的替代数据结构,它们的最坏情况复杂度相当好理解[3],[4],[5],[8]。相反,即使是这些方案中最基本的方案,其平均行为仍然是一个悬而未决的问题[6]。本文的目的是确定几种众所周知的集合合并算法的平均行为。 P>
机译:使用合并算法扩展来自异构实验室平台和同类人群的单个患者生物标志物数据的汇总分析范围
机译:用于近似字符串匹配的改进算法(扩展摘要)
机译:图像直方图和连接组件的并行算法与实验研究(扩展摘要)
机译:一种计算最佳磁盘合并模式的有效算法。 (扩展摘要)
机译:用于将一组划分为一组非降序基数的数据结构和算法。
机译:扩展目标概率假设密度滤波器的两种测量集划分算法
机译:与学位集相关的学位序列:扩展摘要(计算机科学和算法的数学基础和应用)