Random Surfing Revisited: Generalizing PageRank's Teleportation Model

TL;DR

This paper revisits the PageRank teleportation model, introducing NCDawareRank, a new framework that leverages network meta-information and higher-order structures to improve robustness, flexibility, and effectiveness in network centrality.

Contribution

The paper proposes NCDawareRank, a novel ranking framework that generalizes PageRank's teleportation, incorporating network meta-information and higher-order structures while maintaining computational efficiency.

Findings

NCDawareRank exhibits enhanced robustness and flexibility.

The model maintains computational efficiency similar to PageRank.

Experimental results confirm improved centrality measurement performance.

Abstract

We revisit the Random Surfer model, focusing on its--often overlooked--Teleportation component, and we introduce NCDawareRank; a novel ranking framework designed to exploit network meta-information as well as aspects of its higher-order structural organization in a way that preserves the mathematical structure and the attractive computational characteristics of PageRank. A rigorous theoretical exploration of the proposed model reveals a wealth of mathematical properties that entail tangible benefits in terms of robustness, computability, as well as modeling flexibility and expressiveness. A set of experiments on real-work networks verify the theoretically predicted properties of NCDawareRank, and showcase its effectiveness as a network centrality measure.