Empirical Inference Technical Report 2003

Ranking on Data Manifolds

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
Bibtex Type: Technical Report (techreport)
Digital: 0
Electronic Archiving: grant_archive
Institution: Max Planck Institute for Biological Cybernetics, 72076 Tuebingen, Germany
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex

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