Community Detection in Temporal Networks using Triple Nonnegative Matrix Factorization
Published in 2017 International Conference on Mathematics, Modelling and Simulation Technologies and Applications, 2018
This paper introduces a community detection method for temporal networks based on triple nonnegative matrix factorization (Triple-NMF). By incorporating multiple levels of nonnegative matrix factorization, the approach captures both temporal and structural information, enhancing the detection of evolving communities in dynamic networks.