edmot(g_original: object, component_count: int = 2, cutoff: int = 10) → cdlib.classes.node_clustering.NodeClustering¶
The algorithm first creates the graph of higher order motifs. This graph is clustered by the Louvain method.
Supported Graph Types
Undirected Directed Weighted Yes No No Parameters:
- g_original – a networkx/igraph object
- component_count – Number of extracted motif hypergraph components. Default is 2.
- cutoff – Motif edge cut-off value. Default is 10.
>>> from cdlib import algorithms >>> import networkx as nx >>> G = nx.karate_club_graph() >>> coms = algorithms.edmot(G)
Li, Pei-Zhen, et al. “EdMot: An Edge Enhancement Approach for Motif-aware Community Detection.” Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2019.
Reference implementation: https://karateclub.readthedocs.io/