Dynamic community detection model based on representation learning
A technology for detecting models and communities, applied in the field of complex networks, can solve problems such as lack of modeling ability
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[0037] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments.
[0038] refer to figure 1 , a dynamic community detection model based on representation learning, including the following steps:
[0039] S1: Dynamic Network Definition:
[0040] (1): The dynamic network consists of continuous network snapshots G={G 1 ,G 2 ,…,G T} represents, where G represents the entire dynamic network, t ∈ {1, T}, the network snapshot G t ={V t ,E t}, where V t and E t represent the set of nodes and edges in the t snapshot, respectively, {V t+1 ,E t +1} and {V t ,E t} There is no constraint between, i.e. new nodes can join the network and create edges for existing nodes, or previous nodes can disappear from t...
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