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Preprocessing Technique for Cluster Editing via Integer Linear Programming

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Autor(es):
Nogueira Lorena, Luiz Henrique ; Quiles, Marcos Goncalves ; de Leon Ferreira de Carvalho, Andre Carlos Ponce ; Nogueira Lorena, Luiz Antonio ; Huang, DS ; Bevilacqua, V ; Premaratne, P ; Gupta, P
Número total de Autores: 8
Tipo de documento: Artigo Científico
Fonte: INTELLIGENT COMPUTING THEORIES AND APPLICATION, PT I; v. 10954, p. 11-pg., 2018-01-01.
Resumo

This paper addresses the Cluster Editing problem. The objective of this problem is to transform a graph into a disjoint union of cliques using a minimum number of edge modifications. This problem has been considered in the context of bioinformatics, document clustering, image segmentation, consensus clustering, qualitative data clustering among others. Here, we focus on the Integer Linear Programming (ILP) formulation of this problem. The ILP creates models with a large number of constraints. This limits the size of the problems that can be optimally solved. In order to overcome this limitation, this paper proposes a novel preprocessing technique to construct a reduced model that feasibly maintains the optimal solution set. In comparison to the original model, the reduced model preserves the optimal solution and achieves considerable computational time speed-up in the experiments performed on different datasets. (AU)

Processo FAPESP: 11/18496-7 - Aprendizado semi-supervisionado dinâmico e ativo baseado em redes complexas
Beneficiário:Marcos Gonçalves Quiles
Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores