Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization

Abstract

Consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. Consensus clustering (also known as aggregation of clustering) can improve clustering robustness, deal with distributed and heterogeneous data sources and make use of multiple clustering criteria. Semi-supervised clustering can integrate various… (More)
DOI: 10.1109/ICDM.2007.98

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