License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
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DOI: 10.4230/DagSemProc.07071.13
URN: urn:nbn:de:0030-drops-10606
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Kollias, Giorgios ; Gallopoulos, Efstratios

Multidamping simulation framework for link-based ranking

07071.GallopoulosEfstratios.Paper.1060.pdf (0.6 MB)


We review methods for the
approximate computation of PageRank. Standard methods are based on
the eigenvector and linear system characterizations. Our starting
point are recent methods based on series representation whose
coefficients are damping functions, for example Linear Rank,
HyperRank and TotalRank, etc. We propose a multidamping framework
for interpreting PageRank and these methods. Multidamping is based
on some new useful properties of Google type matrices. The approach can
be generalized and could help in the exploration of new
approximations for list-based ranking. This is joint work with Georgios Kollias and is supported by a Pythagoras-EPEAEK-II grant.

BibTeX - Entry

  author =	{Kollias, Giorgios and Gallopoulos, Efstratios},
  title =	{{Multidamping simulation framework for link-based ranking}},
  booktitle =	{Web Information Retrieval and Linear Algebra Algorithms},
  pages =	{1--17},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7071},
  editor =	{Andreas Frommer and Michael W. Mahoney and Daniel B. Szyld},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-10606},
  doi =		{10.4230/DagSemProc.07071.13},
  annote =	{Keywords: PageRank, Google, power method, eigenvalues, teleportation, list-based ranking, TotalRank}

Keywords: PageRank, Google, power method, eigenvalues, teleportation, list-based ranking, TotalRank
Collection: 07071 - Web Information Retrieval and Linear Algebra Algorithms
Issue Date: 2007
Date of publication: 28.06.2007

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