Behavior Query Discovery in System-Generated Temporal Graphs
Summary: Introduces TGMiner, a discriminative temporal-graph pattern miner that converts system logs into reusable query templates over heterogeneous, time-stamped interactions. Leveraging temporal growth-trend pruning, it prunes redundant patterns, delivering 6–32× speedups with expert-validated patterns at 97% precision and 91% recall. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Bo Zong
- 2. Xusheng Xiao
- 3. Xifeng Yan
- 4. Zhichun Li
- 5. Ambuj K. Singh
- 6. Zhenyu Wu
- 7. Guofei Jiang
- 8. Zhiyun Qian
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,276 | AGIS: Fast Approximate Graph Pattern Mining with Structure-Informed Sampling | 2026 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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