Samplesort: A Sampling Approach to Minimal Storage Tree Sorting
Samplesort: A Sampling Approach to Minimal Storage Tree Sorting
复制标题
Samplesort：最小存储树排序的采样方法
DOI：
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发表时间：
1970
期刊：
影响因子：
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通讯作者：
A. C. McKellar
中科院分区：
文献类型：
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作者：
W. D. Frazer;A. C. McKellar
当前正在使用的方法和以前提出的用于在最小的存储树中选择的方法是实现方法的方法，以使序列中位数的效率低下，通过在随机样本选择中有效地使用该信息。在要分类的序列输入过程中，可以对普通最小的存储树排序进行显着改进。
提出了一个过程，该过程是最小存储树排序的概括，并且具有以下三个属性：（a）在预期的比较数量的比较数量来分类输入序列所需的比较数量中，有显着改进（比普通最小的存储树排序）。 （b）该过程在统计上对输入序列中的偏差不敏感。因此，需要进行比较。
The methods currently in use and previously proposed for the choice of a root in minimal storage tree sorting are in reality methods for making inefficient statistical estimates of the median of the sequence to be sorted. By making efficient use of the information in a random sample chosen during input of the sequence to be sorted, significant improvements over ordinary minimal storage tree sorting can be made.
A procedure is proposed which is a generalization of minimal storage tree sorting and which has the following three properties: (a) There is a significant improvement (over ordinary minimal storage tree sorting) in the expected number of comparisons required to sort the input sequence. (b) The procedure is statistically insensitive to bias in the input sequence. (c) The expected number of comparisons required by the procedure approaches (slowly) the information-theoretic lower bound on the number of comparisons required. The procedure is, therefore, “asymptotically optimal.”