An efficient algorithm for computing the distance between close partitions

Citations of this article
Mendeley users who have this article in their library.


A K-partition of a set S is a splitting of S into K non-overlapping classes that cover all elements of S. Numerous practical applications dealing with data partitioning or clustering require computing the distance between two partitions. Previous articles proved that one can compute it in polynomial timeminimum O(|S|+K2) and maximum O(|S|+K3)using a reduction to the linear assignment problem. We propose several conditions for which the partition distance can be computed in O(|S|) time. In practical terms, this computation can be done in O(|S|) time for any two relatively resembling partitions (i.e. with distance less than |S|5) except specially constructed cases. Finally, we prove that, even if there is a bounded number of classes for which the proposed conditions are not satisfied, one can still preserve the linear complexity by exploiting decomposition properties of the similarity matrix. © 2010 Elsevier B.V. All rights reserved.




Porumbel, D. C., Hao, J. K., & Kuntz, P. (2011). An efficient algorithm for computing the distance between close partitions. Discrete Applied Mathematics, 159(1), 53–59.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free