Community detection using fast low-cardinality semidefinite programming

摘要

Community detection for a network using low-cardinality semidefinite programming is described. Data descriptive of a set of nodes of a network is received. The data includes a set of nodes representing entities of a system and edges representing connections between the entities of the system. A modularity maximization is performed to assign each node of the set of nodes to one or more communities to generate multiple-cardinality embeddings. The multiple-cardinality embeddings are rounded to unit cardinality to recover a community assignment with maximum modularity. The community assignment is refined and aggregated to create an aggregate network defining a set of connected communities of the network. The network is operated on in accordance with the community assignment.