BEAR: Block Elimination Approach for
Random Walk with Restart on Large Graphs

Overview

Bear is a novel method for fast, scalable, and accurate random-walk-with-restart (RWR) computation on large graphs.
Bear has two versions:

Paper

BearS is described in the following paper:


BearD is described in the following paper:


Code

The binary codes used in the papers are available.


Datasets

Name#Nodes#EdgesDescriptionSourceDownload
Routing23K48K Internet structure Mark Newman's webpage Link
Citation31K120K Coauthorship network Mark Newman's webpage Link
Trust132K841K Trust network Stanford Large Network Dataset Collection Link
Email265K420K Email network Stanford Large Network Dataset Collection Link
Web-Stan282K2.3M Hyperlink network Stanford Large Network Dataset Collection Link
Web-Notre326K1.5M Hyperlink network Stanford Large Network Dataset Collection Link
Web-BS685K7.6M Hyperlink network Stanford Large Network Dataset Collection Link
Talk2.4M5.0M Talk network Stanford Large Network Dataset Collection Link
Citation3.7M16.5M Patent citation network Stanford Large Network Dataset Collection Link
R-MAT (pul=0.5)100K500K Synthetic graph Link
R-MAT (pul=0.6)100K500K Synthetic graph Link
R-MAT (pul=0.7)100K500K Synthetic graph Link
R-MAT (pul=0.8)100K500K Synthetic graph Link
R-MAT (pul=0.9)100K500K Synthetic graph Link

People