Unsupervised framework for evaluating structural node embeddings of graphs

DOI10.1007/978-3-031-32296-9_3arXiv2306.10770OpenAlexW4376608267MaRDI QIDQ6057288

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Publication date: 4 October 2023

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2306.10770

zbMATH Keywords

node embeddingsstructural node embeddings

Mathematics Subject Classification ID

Graph theory (including graph drawing) in computer science (68R10) Computational aspects of data analysis and big data (68T09)

Cites Work

• Machine learning in social networks. Embedding nodes, edges, communities, and graphs
• An unsupervised framework for comparing graph embeddings
• A Scalable Unsupervised Framework for Comparing Graph Embeddings
• Mining Complex Networks

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