Evolutionary tree spectral clustering

Abstract

Existing evolutionary clustering algorithms are mostly based on temporal smoothness. Yet it is still a difficult problem to find out the rule from the evolutionary data. In this paper, we try to solve this problem by using an evolutionary tree to describe the evolution process of data. Based on evolutionary tree, the structural smoothness is proposed. By taking account of both the existing temporal smoothness and the structural smoothness, we propose an evolutionary tree clustering framework and an evolutionary tree spectral clustering algorithm. Moreover, we analyze the cost function and the solution of evolutionary tree spectral clustering algorithm. Promising experiments on both artificial and real-world datasets demonstrate the superior performance of our proposed method.