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Efficient Graph Embedding Generation and Update for Large-Scale Temporal Graph

Summary: Introduce Temporal-based Bipartite Graph and temporal preferential-attachment similarity (TPASim) to encode concurrent node activity for temporal graph embeddings. LTGE factorizes a 2m-sparse temporal matrix provably equivalent to dense TPASim (reducing complexity by n^2/m) and LTGEInc uses an incremental SVD with guarantees to update embeddings, scaling to 17M nodes/1.3B edges and outperforming prior temporal methods. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
14248
Venue
VLDB
Year
2025
Pagerank
4.1945683e-05
Overall Rank
10,885 | 24.28%
DOI
10.14778/3717755.3717756

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Rank Citing Paper Year Venue Pagerank
10,091 LLM-Powered Interactive Graph Search: A Scalable and Practical Approach 2026 SIGMOD 4.1945683e-05
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