Recommendation model based on opinion diffusion

TL;DR

This paper introduces a diffusion-based recommendation model that incorporates user ratings into a transition matrix and uses a Green function method for faster computation, demonstrating superior prediction accuracy on benchmark data.

Contribution

The paper presents a novel diffusion-based recommendation approach with an efficient Green function method, improving prediction performance over standard methods.

Findings

Superior prediction accuracy on benchmark data

Efficient computation via Green function method

Effective integration of user ratings into diffusion model

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.