This repository contains a reference implementation of the algorithm for Mining Stable Communities in Temporal Networks by Density-based Clustering.
Codes run on Python 2.7 or later
You may use Git to clone the repository from GitHub and run it manually like this:
git clone https://github.com/qinhc/tSCAN.git
cd tSCAN
pip install networkx
pip install click
python run.py
We focus on mining the temporal networks so each edges are associated with a timestamp. Temporal edges are stored at the raw data in which each line is one temporal edge.
| from_id | \t | to_id | \t | timestamps |
|---|
You can type in dataset name, parameters epsilon, tau, miu and method name to control the program:
Dataset name(str): chess_year
Epsilon(float): 0.5
Tau(int): 3
Miu(int): 3
Type one number to chose the algorithm: [1]TSCANB; [2]TSACNS; [3]TSCANA. (int): 1
7301
55899
temporal edges:62385.0
Runing time of SCANB:0.529084
Cores output at: chess_year.output-0.5-3-3_SCANB