Non-negative Matrix Factorisation for Network Reordering
- Autores: Clare M. Lee, Desmond J. Higham, Daniel Crowther, J. Keith Vass
- Localización: Monografías de la Real Academia de Ciencias Exactas, Físicas, Químicas y Naturales de Zaragoza, ISSN 1132-6360, Nº. 33, 2010, págs. 39-53
- Idioma: inglés
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Resumen
Non-negative matrix factorisation covers a variety of algorithms that attempt to represent a given, large, data matrix as a sum of low rank matrices with a prescribed sign pattern. There are intuitave advantages to this approach, but also theoretical and computational challenges. In this exploratory paper we investigate the use of non-negative matrix factorisation algorithms as a means to reorder the nodes in a large network. This gives a set of alternatives to the more traditional approach of using the singular value decomposition. We describe and implement a range of recently proposed algorithms and evaluate their performance on synthetically constructed test data and on a real data set arising in cancer research.
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