LBSA

These codes are for our paper "Locally-biased Spectral Approximation for Community Detection"

Requirements

Before compiling codes, the following software should be installed in your system.

• Matlab
• gcc (for Linux and Mac) or Microsoft Visual Studio (for Windows)

Datasets Information

• SNAP datasets (available at http://snap.stanford.edu/data/)
• LFR benchmark graphs (available at http://sites.google.com/site/santofortunato/inthepress2/)

Example dataset

• Amazon dataset (available at http://snap.stanford.edu/data/com-Amazon.html)
• nodes: 334863, edges: 925872
• nodes are products, edges are co-purchase relationships
• top 5000 communities with ground truth size >= 3

How to run LBSA algorithm

$ cd LBSA_codes 
$ matlab 
$ mex -largeArrayDims GetLocalCond.cpp   % compile the mex file 
$ mex -largeArrayDims rwvec_mex.cpp   % compile the mex file 
$ mex -largeArrayDims pprvec_mex.cpp   % compile the mex file 
$ mex -largeArrayDims hkvec_mex.cpp   % compile the mex file 
$ LBSA(sampleMode,algsMode) 

Command Options for LBSA algorithm:

sampleMode: sampling method (random walk, personalized PageRank and heat kernel diffusion)

algsMode: locally-biased spectral approximation algorithm (Lanczos method or power iteration)

How to run baseline algorithms

run LEMON algorithm

$ cd baseline_codes/LEMON
$ matlab 
$ LEMON

run LOSP algorithm

$ cd baseline_codes/LOSP 
$ matlab 
$ LOSP

run HK algorithm

$ cd baseline_codes/HK
$ matlab 
$ mex -largeArrayDims hkgrow_mex.cpp   % compile the mex file 
$ HK

run PR algorithm

$ cd baseline_codes/PR
$ matlab 
$ mex -largeArrayDims pprgrow_mex.cc   % compile the mex file 
$ PR

Announcements

Licence

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://fsf.org/.

Notification

Please email to panshi@hust.edu.cn or setup an issue if you have any problems or find any bugs.

Acknowledgement

In the program, we incorporate some open source codes as baseline algorithms from the following websites:

• LEMON
• LOSP
• HK
• PR