Finding community structure in very large networks
2004年12月6日 · Here we present a hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with vertices and edges is where is the depth of the dendrogram describing the community structure.
The discovery and analysis of community structure in networks is a topic of considerable recent interest within the physics community, but most methods proposed so far are unsuitable for very large networks because of their computational cost. Here we present a hierarchical agglomeration algorithm for detecting
Finding community structure in very large networks.
2004年8月9日 · It is demonstrated that the algorithms proposed are highly effective at discovering community structure in both computer-generated and real-world network data, and can be used to shed light on the sometimes dauntingly complex structure of networked systems. Defining and identifying communities in networks.
Finding community structure in very large networks - PubMed
The discovery and analysis of community structure in networks is a topic of considerable recent interest within the physics community, but most methods proposed so far are unsuitable for very large networks because of their computational cost. …
Finding community structure in very large networks.[J]
Here we present a hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O(m d log n) where d is the depth of the dendrogram describing the community structure.
The discovery and analysis of community structure in networks is a topic of considerable recent interest within the physics community , but most methods proposed so far are unsuitable for very large networks because of their computational cost. Here we present a hierarchical agglomeration algorithm for detecting
Finding community structure in very large networks - ADS
Here we present a hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O (mdlogn) where d is the depth of the dendrogram describing the community structure.
Finding community structure in very large networks
2005年1月1日 · In this study, we address these issues by proposing a novel network community structure similarity index (NCSSI) based on the edit distance concept.
Finding community structure in very large networks
Here we present a hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O(md log n) where d is the depth of the dendrogram describing the community structure.
Fast unfolding of communities in large networks: 15 years later
2024年10月28日 · Community detection is an algorithmic problem that aims to find the community structure of a network. As such, ... In complex networks, the presence of very large degree vertices (or hubs) makes vertices/edges distribution more complex. Second, if the ends of an edge are not on the same process, messages will have to be sent to synchronize them ...