Lee, Clare and Higham, Desmond and Crowther, D. and Vass, J. Keith
(2010)
*Non-negative matrix factorisation for network reordering.*
Monografias de la Real Academia de Ciencias de Zaragoza, 33.
pp. 39-53.

## Abstract

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.

Item type: | Article |
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ID code: | 29581 |

Notes: | Special issue honoring Manuel Calvo on his 65th birthday |

Keywords: | matrix factorisation , data matrix , cancer research, Probabilities. Mathematical statistics |

Subjects: | Science > Mathematics > Probabilities. Mathematical statistics |

Department: | Faculty of Science > Mathematics and Statistics |

Depositing user: | Pure Administrator |

Date Deposited: | 29 Mar 2011 15:50 |

Last modified: | 21 May 2015 13:07 |

Related URLs: | |

URI: | http://strathprints.strath.ac.uk/id/eprint/29581 |

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