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Found 3 papers, 1 papers with code
Unsupervised embedding of trajectories captures the latent structure of scientific migration
Here, we demonstrate the ability of the model word2vec to encode nuanced relationships between discrete locations from migration trajectories, producing an accurate, dense, continuous, and meaningful vector-space representation.
Persona2vec: A Flexible Multi-role Representations Learning Framework for Graphs
Graph embedding techniques, which learn low-dimensional representations of a graph, are achieving state-of-the-art performance in many graph mining tasks.
Trading characteristics of member firms on the Korea Exchange
The network analysis supports that the members are clustered into three groups similar to DIMs, DSMs, and FRMs.
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