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)
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Authors
- 1. Yifan Song
- 2. Xiaolong Chen
- 3. Wenqing Lin
- 4. Jia Li
- 5. Chen Zhang
- 6. Yan Zhou
- 7. Lei Chen
- 8. Jing Tang
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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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