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Clustering to Given Connectivities

Authors :
Petr A. Golovach and Dimitrios M. Thilikos
Golovach, Petr A.
Thilikos, Dimitrios M.
Petr A. Golovach and Dimitrios M. Thilikos
Golovach, Petr A.
Thilikos, Dimitrios M.
Publication Year :
2019

Abstract

We define a general variant of the graph clustering problem where the criterion of density for the clusters is (high) connectivity. In Clustering to Given Connectivities, we are given an n-vertex graph G, an integer k, and a sequence Lambda=<lambda_{1},...,lambda_{t}> of positive integers and we ask whether it is possible to remove at most k edges from G such that the resulting connected components are exactly t and their corresponding edge connectivities are lower-bounded by the numbers in Lambda. We prove that this problem, parameterized by k, is fixed parameter tractable, i.e., can be solved by an f(k)* n^{O(1)}-step algorithm, for some function f that depends only on the parameter k. Our algorithm uses the recursive understanding technique that is especially adapted so to deal with the fact that we do not impose any restriction to the connectivity demands in Lambda.

Details

Database :
OAIster
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1358726617
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.4230.LIPIcs.IPEC.2019.18