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Improved algorithms for the random cluster graph model

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2002) 2368 230-239
DOI: 10.1007/3-540-45471-3_24
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Abstract

The following probabilistic process models the generation of noisy clustering data: Clusters correspond to disjoint sets of vertices in a graph. Each two vertices from the same set are connected by an edge with probability p, and each two vertices from different sets are connected by an edge with probability r

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Shamir, R., & Tsur, D. (2002). Improved algorithms for the random cluster graph model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2368, pp. 230–239). Springer Verlag. https://doi.org/10.1007/3-540-45471-3_24

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