Correlation clustering and two-edge-connected augmentation for planar graphs

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In correlation clustering, the input is a graph with edge-weights, where every edge is labelled either + or - according to similarity of its endpoints. The goal is to produce a partition of the vertices that disagrees with the edge labels as little as possible. In two-edge-connected augmentation, the input is a graph with edge-weights and a subset R of edges of the graph. The goal is to produce a minimum weight subset S of edges of the graph, such that for every edge in R, its endpoints are two-edge-connected in R ∪ S. For planar graphs, we prove that correlation clustering reduces to two-edge-connected augmentation, and that both problems have a polynomial-time approximation scheme.

Original languageEnglish
Title of host publication32nd International Symposium on Theoretical Aspects of Computer Science, STACS 2015
EditorsErnst W. Mayr, Nicolas Ollinger
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
Pages554-567
Number of pages14
ISBN (Electronic)9783939897781
DOIs
Publication statusPublished - 1 Feb 2015
Event32nd International Symposium on Theoretical Aspects of Computer Science, STACS 2015 - Garching, Germany
Duration: 4 Mar 20157 Mar 2015

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume30
ISSN (Print)1868-8969

Conference

Conference32nd International Symposium on Theoretical Aspects of Computer Science, STACS 2015
Country/TerritoryGermany
CityGarching
Period4/03/157/03/15

Keywords

  • Correlation clustering
  • Planar graphs
  • Polynomialtime approximation scheme
  • Two-edge-connected augmentation

Fingerprint

Dive into the research topics of 'Correlation clustering and two-edge-connected augmentation for planar graphs'. Together they form a unique fingerprint.

Cite this