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Journal article

Heat conduction process on community networks as a recommendation model

  • Zhang, Yi-Cheng Physics Department, University of Fribourg, 1700 Fribourg, Switzerland and Physics Department, Renmin University, Beijing, China
  • Blattner, Marcel Physics Department, University of Fribourg, 1700 Fribourg, Switzerland and Physics Department, Renmin University, Beijing, China
  • Yu, Yi-Kuo National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
    11.10.2007
Published in:
  • Physical Review Letters. - 2007, vol. 99, no. 15, p. 154301
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.
English 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.
Faculty
Faculté des sciences et de médecine
Department
Département de Physique
Language
  • English
Classification
Physics
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/300533
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