On Clustering Using Random Walks

Abstract. We propose a novel approach to clustering, based on deterministic analysis of random walks on the weighted graph associated with the clustering problem. The method is centered around what we shall call separating operators, which are applied repeatedly to sharpen the distinction between the weights of inter-cluster edges (the so-called separators), and those of intra-cluster edges. These operators can be used as a stand-alone for some problems, but become particularly powerful when embedded in a classical multi-scale framework and/or enhanced by other known techniques, such as agglomerative clustering. The resulting algorithms are simple, fast and general, and appear to have many useful applications.

• Type: Conference
• Year: 2001
• Where: FSTTCS
• Authors: David Harel, Yehuda Koren
• Keywords: Classical Multi-scale Framework, Clustering Problem, FSTTCS 2001, Software Engineering, Weighted Graph