Table 3 Modularity of extended graph datasets.
From: Isolate sets partition benefits community detection of parallel Louvain method
Datasets | Modularity (NMI) | ||
|---|---|---|---|
Sequential Louvain method | Hash-table-based method | Isolate-set-based method | |
Amazon0302 | 0.8998 | 0.8969 | 0.9017 |
Amazon0312 | 0.8720 | 0.8677 | 0.8759 |
Amazon0505 | 0.8664 | 0.8713 | 0.8765 |
Amazon0601 | 0.8691 | 0.8721 | 0.8776 |
as-skitter | 0.8132 | 0.8312 | 0.8506 |
cit-Patents | 0.8114 | 0.8102 | 0.8136 |
amazon.ungraph | 0.9262 (0.1240) | 0.9248 (0.1182) | 0.9261 (0.1240) |
com-dblp.ungraph | 0.8203 (0.1345) | 0.8155 (0.1301) | 0.8211 (0.1345) |
com-lj.ungraph | 0.7163 | 0.7204 | 0.7504 |
com-orkut.ungraph | 0.6614 (0.0633) | 0.6987 (0.0645) | 0.6567 (0.0627) |
com-youtube.ungraph | 0.7103 | 0.6909 | 0.7189 |
Gowalla-edges | 0.6889 | 0.6839 | 0.7115 |
soc-LiveJournal1 | 0.7284 | 0.7287 | 0.7558 |
soc-pokec-relationships | 0.6895 | 0.7122 | 0.7166 |
web-Google | 0.9777 | 0.9768 | 0.9776 |
orkut-groupmemberships | 0.3071 | 0.3042 | 0.3138 |
enwiki-2013 | 0.6534 | 0.6304 | 0.6605 |
wikipedia-link-en | 0.3618 | 0.3817 | 0.3706 |
