Dynamic Graph Clustering Using Minimum-Cut Trees

Authors:
Robert Görke;Tanja Hartmann;Dorothea Wagner
Affiliations:
Faculty of Informatics, Universität Karlsruhe (TH), Karlsruhe Institute of Technology (KIT),;Faculty of Informatics, Universität Karlsruhe (TH), Karlsruhe Institute of Technology (KIT),;Faculty of Informatics, Universität Karlsruhe (TH), Karlsruhe Institute of Technology (KIT),
Venue:
WADS '09 Proceedings of the 11th International Symposium on Algorithms and Data Structures
Year:
2009

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Abstract

Algorithms or target functions for graph clustering rarely admit quality guarantees or optimal results in general. Based on properties of minimum-cut trees, a clustering algorithm by Flake et al. does however yield such a provable guarantee. We show that the structure of minimum-s -t -cuts in a graph allows for an efficient dynamic update of minimum-cut trees, and present a dynamic graph clustering algorithm that maintains a clustering fulfilling this quality quarantee, and that effectively avoids changing the clustering. Experiments on real-world dynamic graphs complement our theoretical results.