/MSQC

Mining Stable Quasi-Cliques on Temporal Networks, which is published in TSMC 2022

Primary LanguageC++

Code for MSQC Algorithm

This repository contains a reference implementation of the algorithms for the paper:

Longlong Lin, Pingpeng Yuan, Rong-Hua Li, Jifei Wang, Ling Liu, Hai jin. Mining Stable Quasi-Cliques on Temporal Networks. IEEE Transactions on Systems Man Cybernetics-Systems

Environment

Codes run on C++11 or later. When we run codes on linux, -O2 is recommended to optimizate compilation.

Dataset file format

Input file format

  • The input file should be started with V and E

    • V: upper limit of node id or higher

    • E: the number of edges

  • For each event, there are 3 parameters: vertex1, vertex2, time

    • vertex1, vertex2: the vertices of the changing edge

    • time: the time when the event happens

  • the time of any (vertex1,vertex2) must be sorted in ascending order

Output file format

  • There are two output files

    • TGRA.txt : store the spent time of TGRA algorithm

    • res.(dataset) : dataset refers to dataset name, stroe the spent time of B&B algorithm

  • No matter how many times BB.cpp is excuted, we can get only one TGRA.txt file. That means TGRA.txt stores all TGRA algorithm result.

  • res.(dataset) is different, results of different parameters of one dataset share one dataset. That means one dataset outputs one res.(dataset) file.

Compile and run

  1. create an excutable application by compiling "BB.cpp", for example: g++ -o test BB.cpp

  2. run the excutable application with 5 parameters, which are input file name, gamma, mode, rho, theta, for example: ./test enron 0.8 4 0.6 3

    • input file name: the name of the file describing the tempral graph

    • gamma

    • mode: five pruning algorithms

    • tho

    • theta