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Improved algorithms for the random cluster graph model
Author(s) -
Shamir Ron,
Tsur Dekal
Publication year - 2007
Publication title -
random structures and algorithms
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.314
H-Index - 69
eISSN - 1098-2418
pISSN - 1042-9832
DOI - 10.1002/rsa.20181
Subject(s) - cluster analysis , disjoint sets , random graph , struct , combinatorics , range (aeronautics) , algorithm , mathematics , graph , computer science , cluster (spacecraft) , discrete mathematics , artificial intelligence , materials science , composite material , programming language
We model noisy clustering data using random graphs: Clusters correspond to disjoint sets of vertices. Two vertices from the same set (resp., different sets) share an edge with probability p (resp., r < p ). We give algorithms that reconstruct the clusters from the graph with high probability. Compared to previous studies, our algorithms have lower time complexity and apply under wider parameter range. © 2007 Wiley Periodicals, Inc. Random Struct. Alg., 2007