Code for DLCP Algorithm

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

Longlong Lin, Pingpeng Yuan, Rong-Hua Li, Hai jin. Mining Diversified Top-r Lasting Cohesive Subgraphs on Temporal Networks. IEEE Transactions on Big Data

Environment Setup

Codes run on Python 3.7 or later. PyPy compiler is recommended because it can make the computations quicker without change the codes.

Dateset description

We focus on mining the temporal network so each edge is 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

Running example

python DLCP.py