CoDeSEG Community Detection Package
Project description
Community Detection in Large-Scale Complex Networks via Structural Entropy Game (CoDeSEG)
CoDeSEG supports undirected, directed, weighted, unweighted, overlapping, non-overlapping, and dynamic community detection. The relevant parameter descriptions are as follows:
| Parameter | Description | Type | Default | Required |
|---|---|---|---|---|
in_path |
Input file of graph edge list | file | None | Yes |
out_path |
Output file of communities | file | None | Yes |
ground_truth |
Ground truth file | file | No | No |
weighted |
Weighted graph | bool | false | No |
directed |
directed graph | bool | false | No |
dynamic |
dynamic graph | bool | false | No |
overlap |
Overlapping communities | bool | false | No |
gamma |
Overlapping detecting factor | float | 1.0 | No |
tau |
Non-overlapping entropy threshold | float | 0.3 | No |
r |
Stable round threshold for dynamic detection | int | 2 | No |
it |
Maximum number of iterations | int | 10 | No |
parallel |
Number of threads | int | 1 | No |
verbose |
Print detection iteration messages | bool | false | No |
Note
The format of the input edge list is as follows:
1 \t 2 \n
1 \t 3 \n
2 \t 3 \n
For dynamic graphs, the input should be a file containing edge lists of multiple network snapshots, stored in the /data/ntwk directory. The file structure is as follows:
data(your dataset)/
├── ntwk
├── 1.txt
├── 2.txt
├── 3.txt
...
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