γ-clustering problems: Classical and parametrized complexity

We introduce the γ-clustering problems, which are variants of the well-known Cluster Editing/Deletion/Completion problems, and defined as: given a graph G, how many edges must be edited in G, deleted from G, or added to G in order to have a disjoint union of γ-quasi-cliques. We provide here the complete complexity classification of these problems along with FPT algorithms parameterized by the number of modifications, for the NP-complete problems. We also study here a variant of these problems where the number of final clusters is a fixed constant, obtaining mostly the same results regarding classical and parameterized complexity.

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Journal
Theoretical Computer Science
Published
2024-08-22
DOI
https://doi.org/10.1016/j.tcs.2024.114784
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

γ-clustering problems: Classical and parametrized complexity

Hamida Seba, Antoine Castillon, Clarisse Dhaenens, Julien Baste et al.
Theoretical Computer Science
Complex Network Analysis Techniques
article

γ-clustering problems: Classical and parametrized complexity

Hamida Seba, Antoine Castillon, Clarisse Dhaenens, Julien Baste, Mohammed Haddad
article en

Abstract

We introduce the γ-clustering problems, which are variants of the well-known Cluster Editing/Deletion/Completion problems, and defined as: given a graph G, how many edges must be edited in G, deleted from G, or added to G in order to have a disjoint union of γ-quasi-cliques. We provide here the complete complexity classification of these problems along with FPT algorithms parameterized by the number of modifications, for the NP-complete problems. We also study here a variant of these problems where the number of final clusters is a fixed constant, obtaining mostly the same results regarding classical and parameterized complexity.

Theoretical Computer ScienceVol. 1018
Université Claude Bernard Lyon 1 (FR), Centre National de la Recherche Scientifique (FR), Université de Lille (FR), Centre de Recherche en Informatique (FR), LabEx PERSYVAL-Lab (FR), Laboratoire d'Informatique en Images et Systèmes d'Information (FR), Institut National des Sciences Appliquées de Lyon (FR), École Centrale de Lille (FR)
Agence Nationale de la Recherche
Openalex Percentile: Top 87%
Complex Network Analysis Techniques
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γ-clustering problems: Classical and parametrized complexity — Hamida Seba, Antoine Castillon, et al. · Theoretical Computer Science (2024) | TGRS Research Map | TGRS