In short, a library for computing dynamic pagerank. See  and  for further details.
Ryan Rossi and David Gleich: Dynamic PageRank using Evolving Teleportation, Algorithms and Models for the Web Graph, vol. 7323 of LNCS, pages 126-137. Springer, 2012.
David F. Gleich, Ryan A. Rossi, A Dynamical System for PageRank with Time-Dependent Teleportation, Internet Mathematics, 10:1-2, 188-217, 2014.
These codes are research prototypes and may not work for you. No promises. But do email if you run into problems.
Unzip data into dynamic_pagerank directory
Start matlab in the directory where you unzipped the
$ matlab >> setup_paths >> load('data/wiki-24hours');
This should work on Mac OSX (Lion tested) and Ubuntu linux (10.10 tested) with Matlab R2011a.
>> v = normcols(v); >> X = dynamic_pagerank(A,v);
See examples.m for additional examples
Please let us know if you run into any issues.
The package is organized by directory
: All of the main matlab codes (dynamic_pagerank.m,...)
: dynamic ranking codes and figures
: simple models for prediction using Dynamic PageRank
: experimental codes for identifying trends and similar vertices
: codes for computing Granger causality between vertices
: graphs, precomputed data, and script files for extracting and parsing page views
: this information and all the figures
||PageRank dynamical system analytical solution||Fig. 2|
||PageRank dynamical system analytical solution||Fig. 3|
||The intersection similarity plot||Fig. 5|
||Dynamic PageRank time-series plot||Fig. 6-7|
||Performance of Dynamic PageRank for prediction||Tab. 3|
||Cluster dynamic score trends, vertices w/ similar behavior||Fig. 8|
||Granger causality between vertices||Tab. 4|