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An Approximation Algorithm for a Problem of Partitioning a Sequence into Clusters with Restrictions on Their Cardinalities

机译:一种近似算法将序列分成群集的问题,其基数限制

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We consider the problem of partitioning a finite sequence of points in Euclidean space into a given number of clusters (subsequences) minimizing the sum of squared distances between cluster elements and the corresponding cluster centers. It is assumed that the center of one of the desired clusters is the origin, while the centers of the other clusters are unknown and determined as the mean values over clusters elements. Additionally, there are a few structural restrictions on the elements of clusters with unknown centers: (1) clusters form non-overlapping subsequences of the input sequence, (2) the difference between two consecutive indices is bounded from below and above by prescribed constants, and (3) the total number of elements in these clusters is given as an input. It is shown that the problem is strongly NP-hard. A 2-approximation algorithm which runs in polynomial time for a fixed number of clusters is proposed for this problem.
机译:我们考虑将欧几里德空间中的有限点分配到给定数量的聚类(子序列)中将有限数量的问题最小化集群元素和相应的集群中心之间的平方距离之和。假设其中一个所需簇的中心是起源,而另一个集群的中心是未知的并且被确定为簇元件的平均值。此外,对具有未知中心的集群的元素存在一些结构限制:(1)群集形成输入序列的非重叠子序列,(2)两个连续指数之间的差异由下方和上方由规定的常数界定, (3)将这些集群中的元素总数作为输入给出。结果表明,问题是强烈的NP - 硬。提出了一种在多项式时间内运行固定数量的集群的2近似算法。

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