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Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs

Summary: Temporal SIR-GN: unsupervised structural NRL that clusters and aggregates neighbor embeddings per timestamp, temporally aggregates those summaries, and iterates up to d hops to encode evolving structural roles. Linear-time in temporal edges, with theoretical guarantees and empirically superior accuracy and scalability on node classification/regression tasks. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13061
Venue
VLDB
Year
2023
Pagerank
4.3652496e-05
Overall Rank
9,272 | 35.50%
DOI
10.14778/3598581.3598583

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