Paper Title:
An FPT Algorithm for the Correlation Clustering Problem
  Abstract

Given an undirected graph G=(V, E) with real nonnegative weights and + or – labels on its edges, the correlation clustering problem is to partition the vertices of G into clusters to minimize the total weight of cut + edges and uncut – edges. This problem is APX-hard and has been intensively studied mainly from the viewpoint of polynomial time approximation algorithms. By way of contrast, a fixed-parameter tractable algorithm is presented that takes treewidth as the parameter, with a running time that is linear in the number of vertices of G.

  Info
Periodical
Key Engineering Materials (Volumes 474-476)
Edited by
Garry Zhu
Pages
924-927
DOI
10.4028/www.scientific.net/KEM.474-476.924
Citation
X. Xin, "An FPT Algorithm for the Correlation Clustering Problem", Key Engineering Materials, Vols. 474-476, pp. 924-927, 2011
Online since
April 2011
Authors
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