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Accelerating maximal clique search via graph reduction

Published on:

1 November 2023

Primary Category:

Databases

Paper Authors:

Wen Deng,

Weiguo Zheng,

Hong Cheng

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Key Details

Proposes RMCE, a reduction-based framework to accelerate maximal clique enumeration

Develops global reduction techniques to shrink input graph size

Introduces dynamic reduction to minimize subgraph size in recursive calls

Reduces maximality check cost by pruning unnecessary vertices from forbidden set

AI generated summary

Accelerating maximal clique search via graph reduction

This paper proposes a novel framework called RMCE that accelerates the process of finding all maximal cliques in a graph. It does this by developing techniques to reduce the size of the original graph as well as subgraphs that are examined recursively during the search process. This helps prune the search space and avoid redundant computations. The methods include removing low-degree vertices, non-triangle edges, dynamically reducing subgraph size, and minimizing the 'forbidden set' used for maximality checks.

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