Robustness of shallow graph embedding methods for community detection

arXiv:2405.00636 · physics.soc-ph, cs.LG, cs.SI, physics.data-an · Submitted 2024-05-01 · Read on arXiv

physics.soc-ph, cs.LG, cs.SI, physics.data-an

Submitted: 2024-05-01

Updated: 2026-09-09

Comments: Accepted manuscript. Published in Applied Network Science

Journal ref: Appl Netw Sci (2026)

DOI: 10.1007/s41109-026-00825-z

Code: https://github.com/zf-wei/LLECupy

Project page: https://zf-wei.github.io

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Robustness — 47× in this paper · explained in 5 episodes
• Embeddings — 42× in this paper · explained in 2 episodes
• Benchmark — 41× in this paper · explained in 2 episodes
• Clustering — 31× in this paper · explained in 2 episodes
• Core — 13× in this paper · explained in 2 episodes
• Modularity — 6× in this paper · explained in 9 episodes
• Department of Energy — 5× in this paper
• Higher-Order Preserving Embedding — 5× in this paper
• Laplacian Eigenmap — 5× in this paper
• Objective Function — 5× in this paper · explained in 2 episodes
• Locally Linear Embedding — 4× in this paper
• GNNs — 3× in this paper · explained in 2 episodes
• Modularized Non-Negative Matrix Factorization — 3× in this paper
• Vector Representations — 3× in this paper · explained in 2 episodes
• Adjacency Matrix — 2× in this paper · explained in 1 episode
• Adversarial Attacks — 2× in this paper · explained in 1 episode
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Large-Scale Information Network Embedding — 2× in this paper
• Pacific Northwest National Laboratory — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Aggregation Function — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Alternating Optimization Scheme — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Graph Neural Networks (GNNs) — 1× in this paper · explained in 7 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• National Science Foundation — 1× in this paper
• Oak Ridge Institute for Science and Education — 1× in this paper
• Sparsity — 1× in this paper · explained in 4 episodes
• Spectral clustering — 1× in this paper · explained in 2 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes

Sources

• Efficient Estimation of Word Representations in Vector Space

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