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.
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.
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.
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