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Krylov Subspace Approximation for Local Community Detection in Large Networks

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LOSP_Plus

These codes are for our paper "Krylov Subspace Approximation for Local Community Detection in Large Networks"

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

Example dataset

How to run LOSP_Plus algorithm

$ cd LOSP_Plus_codes
$ matlab 
$ mex -largeArrayDims GetLocalCond.c   % compile the mex file 
$ LOSP_Plus(WalkMode,d,k,alpha,TruncateMode,beta) 

Command Options for LOSP_Plus algorithm:

WalkMode: 1: standard, 2: light lazy, 3: lazy, 4: personalized (default: 2)

d: dimension of local spectral subspace (default: 2)

k: number of random walk steps (default: 3)

alpha: a parameter controls random walk diffusion (default: 1)

TruncateMode: 1: truncation by truth size, 2: truncation by local minimal conductance (default: 2)

beta: a parameter controls local minimal conductance (default: 1.02)

How to run baseline algorithms

run LEMON algorithm

$ cd baseline_codes/LEMON
$ matlab 
$ LEMON

run PGDC-d algorithm

$ cd baseline_codes/PGDc-d
$ matlab
$ PGDC_d

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

More comparison

run GLOSP algorithm for evaluating the effectiveness of Krylov subspace approximation

$ cd LOSP_Plus_codes
$ matlab 
$ GLOSP_Plus   % GLOSP algorithm using eigenspace rather than Krylov subspace

run HKL and PRL for evaluating the effectiveness of local minimal conductance truncation

$ cd LOSP_Plus_codes
$ matlab
$ mex -largeArrayDims hkvec_mex.cpp   % compile mex file
$ mex -largeArrayDims pprvec_mex.cc   % compile mex file
$ HK_local    % HKL algorithm based on local minimal conductance truncation
$ PR_local    % PRL algorithm based on local minimal conductance truncation

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:

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