Application of tropical semiring for matrix factorization

Authors

  • Amra Omanović University of Ljubljana, Faculty of Computer and Information Science
  • Polona Oblak University of Ljubljana, Faculty of Computer and Information Science
  • Tomaž Curk University of Ljubljana, Faculty of Computer and Information Science

DOI:

https://doi.org/10.31449/upinf.99

Keywords:

data embedding, data mining, matrix factorization, subtropical semiring, tropical semiring

Abstract

Matrix factorization methods employ standard linear algebra, i.e. linear models, for recommender systems. With the introduction of the tropical semiring, we can achieve non-linearity. We review algorithms that use the tropical semiring for matrix factorization and provide their strengths and limitations. We show that the tropical matrix factorization yields better results than non-negative matrix factorization for the synthetic data created by the underlying process of the tropical semiring.

Published

2020-12-07

How to Cite

[1]
Omanović, A., Oblak, P. and Curk, T. 2020. Application of tropical semiring for matrix factorization. Applied Informatics. 28, 4 (Dec. 2020). DOI:https://doi.org/10.31449/upinf.99.

Issue

Section

Short scientific articles