Recommendation model based on opinion diffusion

Abstract

Information overload in the modern society calls for highly efficient recommendation algorithms. In this letter we present a novel diffusion based recommendation model, with users' ratings built into a transition matrix. To speed up computation we introduce a Green function method. The numerical tests on a benchmark database show that our prediction is superior to the standard recommendation methods.

5 pages, 2 figures

References in corpus (2)

• Heat Conduction Process on Community Networks as a Recommendation Model
• Quantum and classical diffusion in small-world networks

Cited by in corpus (2)

• Effect of initial configuration on network-based recommendation
• Information Filtering via Self-Consistent Refinement