Heat Conduction Process on Community Networks as a Recommendation Model

2007/10/10 by Yi-Cheng Zhang, Yi‐Cheng Zhang, Marcel Blattner +2 · 5 citations
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Opinion Dynamics and Social Influence #Recommender Systems and Techniques #physics.soc-ph

paper · pdf · doi:10.1103/physrevlett.99.154301

published as Phys. Rev. Lett. 99, 154301 (2007) · 4 pages, 2 figures

openalex publication_date 2007/10/10 · arxiv created 2008/03/14 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Using heat conduction mechanism on a social network we develop a systematic method to predict missing values as recommendations. This method can treat very large matrices that are typical of internet communities. In particular, with an innovative, exact formulation that accommodates arbitrary boundary condition, our method is easy to use in real applications. The performance is assessed by comparing with traditional recommendation methods using real data.

Citations

• Evaluating collaborative filtering recommender systems
• The structure and function of complex networks

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