R. Rossi, und D. Gleich. (2012)cite arxiv:1203.6098Comment: WAW 2012.
Zusammenfassung
The importance of nodes in a network constantly fluctuates based on changes
in the network structure as well as changes in external interest. We propose an
evolving teleportation adaptation of the PageRank method to capture how changes
in external interest influence the importance of a node. This framework
seamlessly generalizes PageRank because the importance of a node will converge
to the PageRank values if the external influence stops changing. We demonstrate
the effectiveness of the evolving teleportation on the Wikipedia graph and the
Twitter social network. The external interest is given by the number of hourly
visitors to each page and the number of monthly tweets for each user.
Beschreibung
[1203.6098] Dynamic PageRank using Evolving Teleportation
%0 Generic
%1 rossi2012dynamic
%A Rossi, Ryan A.
%A Gleich, David F.
%D 2012
%K centrality networkanalysis networks pagerank spp temporal temporalnetworks
%T Dynamic PageRank using Evolving Teleportation
%U http://arxiv.org/abs/1203.6098
%X The importance of nodes in a network constantly fluctuates based on changes
in the network structure as well as changes in external interest. We propose an
evolving teleportation adaptation of the PageRank method to capture how changes
in external interest influence the importance of a node. This framework
seamlessly generalizes PageRank because the importance of a node will converge
to the PageRank values if the external influence stops changing. We demonstrate
the effectiveness of the evolving teleportation on the Wikipedia graph and the
Twitter social network. The external interest is given by the number of hourly
visitors to each page and the number of monthly tweets for each user.
@misc{rossi2012dynamic,
abstract = {The importance of nodes in a network constantly fluctuates based on changes
in the network structure as well as changes in external interest. We propose an
evolving teleportation adaptation of the PageRank method to capture how changes
in external interest influence the importance of a node. This framework
seamlessly generalizes PageRank because the importance of a node will converge
to the PageRank values if the external influence stops changing. We demonstrate
the effectiveness of the evolving teleportation on the Wikipedia graph and the
Twitter social network. The external interest is given by the number of hourly
visitors to each page and the number of monthly tweets for each user.},
added-at = {2018-11-01T15:26:19.000+0100},
author = {Rossi, Ryan A. and Gleich, David F.},
biburl = {https://www.bibsonomy.org/bibtex/2f1372f992cf2adfc2988e979f6a0ee91/albinzehe},
description = {[1203.6098] Dynamic PageRank using Evolving Teleportation},
interhash = {b517373b55ea100c9987f957b7e54f7a},
intrahash = {f1372f992cf2adfc2988e979f6a0ee91},
keywords = {centrality networkanalysis networks pagerank spp temporal temporalnetworks},
note = {cite arxiv:1203.6098Comment: WAW 2012},
timestamp = {2018-11-01T15:26:19.000+0100},
title = {Dynamic PageRank using Evolving Teleportation},
url = {http://arxiv.org/abs/1203.6098},
year = 2012
}