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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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