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Dec 17, 2019 · The procedure involves iteratively finding nodes with the highest bridging centrality value and subsequently its neighbours that yield the least ...
Dec 17, 2019 · Patterns of connectivity among nodes on networks can be revealed by community detection algorithms. The great significance of communities in ...
Abstract: Patterns of connectivity among nodes on networks can be revealed by community detection algorithms. The great significance of communities in the ...
Sep 25, 2020 · Here we develop a method that incorporates both the topology of interactions and node attributes to extract communities in multilayer networks.
Abstract: Many methods have been proposed for community detection in networks, but most of them do not take into account additional information on the nodes ...
Jan 29, 2021 · Community detection techniques are useful for social media algorithms to discover people with common interests and keep them tightly connected.
These algorithms seek to identify clusters or communities within a network where nodes are more densely connected to each other than to the rest of the network.
Aug 20, 2020 · In this paper, we propose a novel RWM (Random Walk in Multiple networks) model to find relevant local communities in all networks for a given query node set ...
Here we develop a method that incorporates both the topology of interactions and node attributes to extract communities in multilayer networks.
There are multiple types of nodes and multiple types of node proximities. Complementary information from different networks helps to improve detection accuracy.