TIMEST: Temporal Information Motif Estimator Using Sampling Trees
Summary: TIMEST estimates temporal-motif counts of arbitrary size via weighted sampling over temporal spanning trees, avoiding combinatorial explosion. It provides theoretical guarantees and substantially outperforms exact and approximate baselines in speed and accuracy. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Yunjie Pan (University of Michigan)
- 2. Omkar Bhalerao (University of California Santa Cruz)
- 3. C. Seshadhri (University of California Santa Cruz)
- 4. Nishil Talati (University of Michigan)
BibTeX Citation
@article{pan_vldb26,
title = {{TIMEST: Temporal Information Motif Estimator Using Sampling Trees}},
author = {Pan, Yunjie and Bhalerao, Omkar and Seshadhri, C. and Talati, Nishil},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {1},
pages = {15--28},
doi = {10.14778/3772181.3772183},
url = {https://doi.org/10.14778/3772181.3772183},
year = {2026}
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,103 | Counting and Sampling Triangles from a Graph Stream | 2013 | VLDB | 0.000121583 |
| 3,028 | Motivo: fast motif counting via succinct color coding and adaptive sampling | 2019 | VLDB | 7.8349117e-05 |
| 3,911 | Efficient Temporal Butterfly Counting and Enumeration on Temporal Bipartite Graphs | 2024 | VLDB | 7.0240227e-05 |
| 3,955 | 2SCENT: An Efficient Algorithm for Enumerating All Simple Temporal Cycles | 2018 | VLDB | 6.9950293e-05 |
| 3,997 | Efficient Bi-triangle Counting for Large Bipartite Networks | 2021 | VLDB | 6.9679551e-05 |
| 4,143 | Efficient Biclique Counting in Large Bipartite Graphs | 2023 | SIGMOD | 6.8760066e-05 |
| 11,223 | Everest: GPU-Accelerated System For Mining Temporal Motifs | 2024 | VLDB | 5.093636e-05 |
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