小聚类聚类编辑问题的逼近算法

IF 0.9 4区数学 Q3 MATHEMATICS, APPLIED

Discrete Optimization Pub Date : 2025-06-13 DOI:10.1016/j.disopt.2025.100900

Alexander Kononov , Victor Il’ev

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引用次数: 0

摘要

聚类是将对象分成组（称为集群）的任务，以便同一组中的对象彼此相似。聚类编辑问题是对图进行聚类建模的最自然的方法之一。在该问题中，目标之间的相似关系由一个无向图给出，该无向图的顶点对应于目标，边缘连接相似目标的对，并要求将顶点集划分为不相交的子集，以最小化聚类之间的边数和聚类内部的缺边数。我们提出了新的近似算法，当聚类大小的上界是三个或四个顶点时，它具有更好的最坏情况性能保证。

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Approximation algorithms for the cluster editing problem with small clusters

Clustering is the task of dividing objects into groups (called clusters) so that objects in the same group are similar to each other. The Cluster Editing problem is one of the most natural ways to model clustering on graphs. In this problem, the similarity relation between objects is given by an undirected graph whose vertices correspond to the objects, edges connect couples of similar objects, and it is required to partition the set of vertices into disjoint subsets minimizing the number of edges between clusters and the number of missing edges within clusters. We present new approximation algorithms with better worst-case performance guarantees when cluster sizes are upper bounded by three or four vertices.

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来源期刊

Discrete Optimization 管理科学-应用数学

CiteScore

2.10

自引率

9.10%

发文量

审稿时长

>12 weeks

期刊介绍： Discrete Optimization publishes research papers on the mathematical, computational and applied aspects of all areas of integer programming and combinatorial optimization. In addition to reports on mathematical results pertinent to discrete optimization, the journal welcomes submissions on algorithmic developments, computational experiments, and novel applications (in particular, large-scale and real-time applications). The journal also publishes clearly labelled surveys, reviews, short notes, and open problems. Manuscripts submitted for possible publication to Discrete Optimization should report on original research, should not have been previously published, and should not be under consideration for publication by any other journal.