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Graph Partitioning and Graph Clustering
Edited by: David A. Bader, Georgia Institute of Technology, Atlanta, GA, and Henning Meyerhenke, Peter Sanders, and Dorothea Wagner, Karlsruhe Institute of Technology, Germany

Contemporary Mathematics
2013; 240 pp; softcover
Volume: 588
ISBN-10: 0-8218-9038-7
ISBN-13: 978-0-8218-9038-7
List Price: US$89
Member Price: US$71.20
Order Code: CONM/588
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Graph partitioning and graph clustering are ubiquitous subtasks in many applications where graphs play an important role. Generally speaking, both techniques aim at the identification of vertex subsets with many internal and few external edges. To name only a few, problems addressed by graph partitioning and graph clustering algorithms are:

  • What are the communities within an (online) social network?
  • How do I speed up a numerical simulation by mapping it efficiently onto a parallel computer?
  • How must components be organized on a computer chip such that they can communicate efficiently with each other?
  • What are the segments of a digital image?
  • Which functions are certain genes (most likely) responsible for?

The 10th DIMACS Implementation Challenge Workshop was devoted to determining realistic performance of algorithms where worst case analysis is overly pessimistic and probabilistic models are too unrealistic. Articles in the volume describe and analyze various experimental data with the goal of getting insight into realistic algorithm performance in situations where analysis fails.

This book is published in cooperation with the Center for Discrete Mathematics and Theoretical Computer Science.


Graduate students and research mathematicians interested in graph theory and combinatorial algorithms.

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