Fixed-parameter tractability of graph modification problems for hereditary properties
Information Processing Letters
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Massive Quasi-Clique Detection
LATIN '02 Proceedings of the 5th Latin American Symposium on Theoretical Informatics
Machine Learning
Cluster graph modification problems
Discrete Applied Mathematics - Discrete mathematics & data mining (DM & DM)
A more effective linear kernelization for cluster editing
Theoretical Computer Science
A More Relaxed Model for Graph-Based Data Clustering: s-Plex Editing
AAIM '09 Proceedings of the 5th International Conference on Algorithmic Aspects in Information and Management
Going weighted: Parameterized algorithms for cluster editing
Theoretical Computer Science
Deterministic algorithms for rank aggregation and other ranking and clustering problems
WAOA'07 Proceedings of the 5th international conference on Approximation and online algorithms
The cluster editing problem: implementations and experiments
IWPEC'06 Proceedings of the Second international conference on Parameterized and Exact Computation
Efficient parameterized preprocessing for cluster editing
FCT'07 Proceedings of the 16th international conference on Fundamentals of Computation Theory
Generalized graph clustering: recognizing (p, q)-cluster graphs
WG'10 Proceedings of the 36th international conference on Graph-theoretic concepts in computer science
A More Relaxed Model for Graph-Based Data Clustering: $s$-Plex Cluster Editing
SIAM Journal on Discrete Mathematics
Graph-based data clustering with overlaps
Discrete Optimization
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In the 驴-Cluster Editing problem, one is given an undirected graph G, a density measure 驴, and an integer k 驴 0, and needs to decide whether it is possible to transform G by editing (deleting and inserting) at most k edges into a dense cluster graph. Herein, a dense cluster graph is a graph in which every connected component K = (V K ,E K ) satisfies 驴. The well-studied Cluster Editing problem is a special case of this problem with 驴: ="being a clique". In this work, we consider three other density measures that generalize cliques: 1) having at most s missing edges (s-defective cliques), 2) having average degree at least |V K | 驴 s (average-s-plexes), and 3) having average degree at least μ· (|V K | 驴 1) (μ-cliques), where s and μ are a fixed integer and a fixed rational number, respectively. We first show that the 驴-Cluster Editing problem is NP-complete for all three density measures. Then, we study the fixed-parameter tractability of the three clustering problems, showing that the first two problems are fixed-parameter tractable with respect to the parameter (s,k) and that the third problem is W[1]-hard with respect to the parameter k for 0 μ