Proposes a dynamic network embedding method using random walks and dynamic Bernoulli embeddings to preserve temporal continuity across discrete-time snapshots for network evolution analysis.
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Dynamic Network Embeddings for Network Evolution Analysis
Proposes a dynamic network embedding method using random walks and dynamic Bernoulli embeddings to preserve temporal continuity across discrete-time snapshots for network evolution analysis.