Abstract
Algorithms or target functions for graph clustering rarely admit quality guarantees or optimal results in general. However, a hierarchical clustering algorithm by Flake et al., which is based on minimum s-t-cuts whose sink sides are of minimum size, yields such a provable guarantee. We introduce a new degree of freedom to this method by allowing arbitrary minimum s-t-cuts and show that this unrestricted algorithm is complete, i.e., any clustering hierarchy based on minimum s-t-cuts can be found by choosing the right cuts. This allows for a more comprehensive analysis of a graph’s structure. Additionally, we present a dynamic version of the unrestricted approach which employs this new degree of freedom to maintain a hierarchy of clusterings fulfilling this quality guarantee and effectively avoid changing the clusterings.
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Doll, C., Hartmann, T., Wagner, D. (2011). Fully-Dynamic Hierarchical Graph Clustering Using Cut Trees. In: Dehne, F., Iacono, J., Sack, JR. (eds) Algorithms and Data Structures. WADS 2011. Lecture Notes in Computer Science, vol 6844. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22300-6_29
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DOI: https://doi.org/10.1007/978-3-642-22300-6_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22299-3
Online ISBN: 978-3-642-22300-6
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