Forman-Ricci Flow for Change Detection in Large Dynamic Data Sets

Forman-Ricci Flow for Change Detection in Large Dynamic Data Sets

We present a viable geometric solution for the detection of dynamic effects in complex networks. Building on Forman’s discretization of the classical notion of Ricci curvature, we introduce a novel geometric method to characterize different types of real-world networks with an emphasis on peer-to-pe...

Full description

Bibliographic Details
Main Authors: Melanie Weber, Jürgen Jost, Emil Saucan
Format: Article
Language:English
Published: MDPI AG 2016-11-01
Series:Axioms
Subjects:
Ricci flow
Forman curvature
complex systems
dynamic networks
change detection
peer-to-peer network
Online Access:http://www.mdpi.com/2075-1680/5/4/26
Description
Summary:We present a viable geometric solution for the detection of dynamic effects in complex networks. Building on Forman’s discretization of the classical notion of Ricci curvature, we introduce a novel geometric method to characterize different types of real-world networks with an emphasis on peer-to-peer networks. We study the classical Ricci-flow in a network-theoretic setting and introduce an analytic tool for characterizing dynamic effects. The formalism suggests a computational method for change detection and the identification of fast evolving network regions and yields insights into topological properties and the structure of the underlying data.
ISSN:2075-1680

Similar Items