VERSE
VERtex Similarity Embeddings
2000년 도입 · 논문 40편에서 사용
VERtex Similarity Embeddings (VERSE) is a simple, versatile, and memory-efficient method that derives graph embeddings explicitly calibrated to preserve the distributions of a selected vertex-to-vertex similarity measure. VERSE learns such embeddings by training a single-layer neural network. Source: Tsitsulin et al. Image source: Tsitsulin et al.
출처: VERSE: Versatile Graph Embeddings from Similarity Measures
소개 논문: VERSE: Versatile Graph Embeddings from Similarity Measures
Graph Embeddings · Graphs