Exact Algorithms for Cluster Editing: Evaluation and Experiments

DOI10.1007/978-3-540-68552-4_22zbMath1215.68168OpenAlexW1723005049MaRDI QIDQ3506417

Gunnar W. Klau, Sebastian Böcker, Sebastian Briesemeister

Publication date: 13 June 2008

Published in: Experimental Algorithms (Search for Journal in Brave)

Full work available at URL: https://ir.cwi.nl/pub/14843

Mathematics Subject Classification ID

Integer programming (90C10) Nonnumerical algorithms (68W05) Polyhedral combinatorics, branch-and-bound, branch-and-cut (90C57) Graph theory (including graph drawing) in computer science (68R10)

Related Items (14)

Data reductions, fixed parameter tractability, and random weighted \(d\)-CNF satisfiability ⋮ On Making Directed Graphs Transitive ⋮ Graph-Based Data Clustering with Overlaps ⋮ Cluster Editing ⋮ Polynomial kernels for 3-leaf power graph modification problems ⋮ Kernelization and complexity results for connectivity augmentation problems ⋮ Cluster Editing: Kernelization Based on Edge Cuts ⋮ Efficient algorithms for cluster editing ⋮ A more effective linear kernelization for cluster editing ⋮ Alternative Parameterizations for Cluster Editing ⋮ A More Relaxed Model for Graph-Based Data Clustering: s-Plex Editing ⋮ Kernelization: New Upper and Lower Bound Techniques ⋮ Going weighted: parameterized algorithms for cluster editing ⋮ Going Weighted: Parameterized Algorithms for Cluster Editing

Cites Work

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• Graph-modeled data clustering: Exact algorithms for clique generation
• NP-hard problems in hierarchical-tree clustering
• A cutting plane algorithm for a clustering problem
• Automated generation of search tree algorithms for hard graphs modification problems
• Cluster graph modification problems
• Clustering with qualitative information
• Clustering of microarray data via clique partitioning
• The Cluster Editing Problem: Implementations and Experiments
• A More Effective Linear Kernelization for Cluster Editing
• Deterministic Algorithms for Rank Aggregation and Other Ranking and Clustering Problems
• Going Weighted: Parameterized Algorithms for Cluster Editing

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