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Ranking on Data Manifolds

2003

Technical Report

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The Google search engine has had a huge success with its PageRank web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the World Wide Web using random walk. This algorithm can only be used for graph data, however. Here we propose a simple universal ranking algorithm for vectorial data, based on the exploration of the intrinsic global geometric structure revealed by a huge amount of data. Experimental results from image and text to bioinformatics illustrates the validity of our algorithm.

Author(s): Zhou, D. and Weston, J. and Gretton, A. and Bousquet, O. and Schölkopf, B.
Number (issue): 113
Year: 2003
Month: June
Day: 0

Department(s): Empirical Inference
Bibtex Type: Technical Report (techreport)

Institution: Max Planck Institute for Biological Cybernetics, 72076 Tuebingen, Germany

Digital: 0
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF

BibTex

@techreport{2290,
  title = {Ranking on Data Manifolds},
  author = {Zhou, D. and Weston, J. and Gretton, A. and Bousquet, O. and Sch{\"o}lkopf, B.},
  number = {113},
  organization = {Max-Planck-Gesellschaft},
  institution = {Max Planck Institute for Biological Cybernetics, 72076 Tuebingen, Germany},
  school = {Biologische Kybernetik},
  month = jun,
  year = {2003},
  month_numeric = {6}
}