On this basis, a well-performing algorithm node2vec (Grover and Leskovec, 2016) is adopted to conduct an unsupervised random walk to vectorize every node ∀v * ∈ V into a d-dimensional embedding ϕ(v * ) ∈ R d so that any edge ∀e * ∈ E can be calculated therefrom.
we employ evolutionary algorithm (EA) to tune the EUD, which enjoys advantages over conventional gradient methods in both convergence speed and accuracy.