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Part-Based Data Analysis with Masked Non-negative Matrix Factorization

  • Gabriella Casalino
  • Nicoletta Del Buono
  • Corrado Mencar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8584)

Abstract

We face the problem of interpreting parts of a dataset as small selections of features. Particularly, we propose a novel masked nonnegative matrix factorization algorithm which is used either to explain data as a composition of interpretable parts (which are actually hidden in them) and to introduce knowledge in the factorization process. Numerical examples prove the effectiveness of the proposed algorithm as a useful tool for Intelligent Data Analysis.

Keywords

Nonnegative matrix factorization mask matrix structure retrieval 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Gabriella Casalino
    • 1
  • Nicoletta Del Buono
    • 2
  • Corrado Mencar
    • 1
  1. 1.Department of InformaticsUniversity of BariBariItaly
  2. 2.Department of MathematicsUniversity of BariBariItaly

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