FAST-temporal-motif

This is the source code for our ICDE2022 submission:

ID: 627, Title: Scalable Motif Counting for Large-scale Temporal Graphs.

Fast-temporal-motif is an algorithm proposed to count sub-graphs (i.e., motifs) in temporal graphs. This repository provides the source code of the algorithm. Besides, researchers can directly compile the project to have a quick start to verify the correctness and efficiency of the proposed algorithm.

Compile

Compile the project

download the project, the project looks like:

/FAST-temporal-motif
├── include
│   ├── global.h
│   ├── egeLoader.h
│   ├── starAndPairCount.h
│   ├── triangleCount.h
│   └── convertMartix.h
├── src
│   ├── global.cpp
│   ├── egeLoader.cpp
│   ├── starAndPairCount.cpp
│   ├── triangleCount.cpp
│   ├── convertMartix.cpp
│   └── main.cpp
├── makefile
└── README.md

execute make to compile the project, and get FAST_temporal_motif.exe

make

you can do make clean to remove FAST_temporal_motif.exe and all .o files

make clean

Compile settings

you can modify makefile to change compile settings. The default settings:

compile the project without using OPENMP. You can set the OMPFLAG to true to compile the project into a openmp program if you want it work with multiple threads
use -O3 Optimize

Command line arguments

./FAST_temporal_motif -input -output -f -t -d -w

Argument	Type	Meaning	Required
-input	string	the path of input data file	Yes
-output	string	the path of output file	Yes
-f	int 0/1	single/multiple threads	No default 0
-t	int	the number of threads (when using multiple threads)	No default 1
-d	int	the threshold of degree (when using multiple threads)	No default INT_MAX
-w	int	time window	No default INT_MAX

for example, if you want to count all temporal-motifs within the time span of 600 in input.txt, with 8 threads, thrd=200000 and output results to output.txt, you can run the program as follows:

./FAST_temporal_motif -input input.txt -output output.txt -f 1 -t 8 -d 200000 -w 600

The order of the arguments can be changed

Data file

Input data file

n rows, each row represents a directed edge

3 data in each row, representing node 1, node 2, and timestamp

use space as separator

Output file

a 6*6 martix, each element representing the number of motif instances for $M_{i,j}$ in our paper.

Experiment

Results of our experiments are shown in appendix.pdf

skwn-j/FAST-temporal-motif