2026-07-23T08:19:35Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:1060 2024-03-06T11:07:20Z ddc:004 open_access

Multidamping simulation framework for link-based ranking Kollias, Giorgios Gallopoulos, Efstratios PageRank Google power method eigenvalues teleportation list-based ranking TotalRank 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Giorgios Kollias and Efstratios Gallopoulos 2007 Is Part Of Dagstuhl Seminar Proceedings, Volume 7071, Web Information Retrieval and Linear Algebra Algorithms (2007) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.07071.13 urn:nbn:de:0030-drops-10606 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07071.13 eng https://creativecommons.org/licenses/by/4.0/legalcode