English

On Dasgupta's hierarchical clustering objective and its relation to other graph parameters

Data Structures and Algorithms 2021-05-26 v1

Abstract

The minimum height of vertex and edge partition trees are well-studied graph parameters known as, for instance, vertex and edge ranking number. While they are NP-hard to determine in general, linear-time algorithms exist for trees. Motivated by a correspondence with Dasgupta's objective for hierarchical clustering we consider the total rather than maximum depth of vertices as an alternative objective for minimization. For vertex partition trees this leads to a new parameter with a natural interpretation as a measure of robustness against vertex removal. As tools for the study of this family of parameters we show that they have similar recursive expressions and prove a binary tree rotation lemma. The new parameter is related to trivially perfect graph completion and therefore intractable like the other three are known to be. We give polynomial-time algorithms for both total-depth variants on caterpillars and on trees with a bounded number of leaf neighbors. For general trees, we obtain a 2-approximation algorithm.

Keywords

Cite

@article{arxiv.2105.12093,
  title  = {On Dasgupta's hierarchical clustering objective and its relation to other graph parameters},
  author = {Svein Høgemo and Benjamin Bergougnoux and Ulrik Brandes and Christophe Paul and Jan Arne Telle},
  journal= {arXiv preprint arXiv:2105.12093},
  year   = {2021}
}

Comments

Full version, 19 pages

R2 v1 2026-06-24T02:27:30.427Z