Improved Approximation Algorithms for Bipartite Correlation Clustering
نویسندگان
چکیده
منابع مشابه
Improved Approximation Algorithms for Bipartite Correlation Clustering
In this work we study the problem of Bipartite Correlation Clustering (BCC), a natural bipartite counterpart of the well studied Correlation Clustering (CC) problem. Given a bipartite graph, the objective of BCC is to generate a set of vertex-disjoint bi-cliques (clusters) which minimizes the symmetric difference to it. The best known approximation algorithm for BCC due to Amit (2004) guarantee...
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Bipartite Correlation clustering is the problem of generating a set of disjoint bi-cliques on a set of nodes while minimizing the symmetric difference to a bipartite input graph. The number or size of the output clusters is not constrained in any way. The best known approximation algorithm for this problem gives a factor of 11. This result and all previous ones involve solving large linear or s...
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ژورنال
عنوان ژورنال: SIAM Journal on Computing
سال: 2012
ISSN: 0097-5397,1095-7111
DOI: 10.1137/110848712