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.
['Yi-Cheng Zhang', 'Matus Medo', 'Jie Ren', 'Tao Zhou', 'Tao Li', 'Fan Yang']
Recommendation model based on opinion diffusion