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Local search for diversified Top-k clique search problem

机译:本地搜索各种Top-k集团搜索问题

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The objective of the diversified top-k clique (DTKC) search problem is to find k maximal cliques that cover the maximum number of vertices in a given graph. This problem is equivalent to the well-known maximum clique problem (MaxClique) when k = 1. This paper proves the NP-hardness of the DTKC search problem and presents a local search algorithm, named TOPKLS, based on two novel strategies for the DTKC search problem. The first strategy is called enhanced configuration checking (ECC), which is a new variant of a recent effective strategy called configuration checking (CC), for reducing cycling in the local search and improving the diversity of the DTKC search problem. The second strategy is a heuristic to estimate the quality of each maximal clique. Experiments demonstrate that TOPKLS outperforms the existing algorithms on large sparse graphs from real-world applications. (C) 2019 Elsevier Ltd. All rights reserved.
机译:多样化的top-k集团(DTKC)搜索问题的目的是找到k个最大集团,它们覆盖给定图中最大数量的顶点。当k = 1时,此问题等效于众所周知的最大团组问题(MaxClique)。本文证明了DTKC搜索问题的NP难度,并基于DTKC的两种新颖策略,提出了一种名为TOPKLS的局部搜索算法。搜索问题。第一种策略称为增强配置检查(ECC),它是最近一种称为配置检查(CC)的有效策略的新变体,用于减少本地搜索中的循环并提高DTKC搜索问题的多样性。第二种策略是启发式估计每个最大派系的质量。实验表明,TOPKLS在现实应用中的大型稀疏图中的性能优于现有算法。 (C)2019 Elsevier Ltd.保留所有权利。

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