Code for CCSS Algorithm

This repository contains a reference implementation of the algorithms for the paper: “CCSS: Towards Conductance-based Community Search with Size Constraints”.

Experimental Environment

This code can be run on a Linux environment. Our code is compiled on a Linux server with Intel(R) Xeon(R) Gold 6348 @ 2.60GHz CPU and 256GB RAM running CentOS 7.7.

Dataset Description

We guarantee that the maximum connected component of the original data is taken. The IDs of the vertex are arranged consecutively starting from 0, with the format:

 first_v  second_v

All public datasets can be downloaded from http://snap.stanford.edu/data/index.html

Running Format

python3 -u CCSS.py [1. graph name] [2. iterations] [3. query vid: q][4. size LB: l] [5. size UB: h]

Running Instance

python3 -u CCSS.py graph.txt 2 3 3 4