Community Detection in Social Network with Pairwisely Constrained Symmetric Non-Negative Matrix Factorization

Abstract

Non-negative Matrix Factorization (NMF) aims to find two non-negative matrices whose product approximates the original matrix well, and is widely used in clustering condition with good physical interpretability and universal applicability. Detecting communities with NMF can keep non-negative network physical definition and effectively capture communities-based structure in the low dimensional data space. However some NMF methods in community detection did not concern with more network inner structures or existing ground-truth community information.