On Reporting Durable Patterns in Temporal Proximity Graphs
Summary: Near-linear-time algorithms with provable guarantees to report approximately durable subgraph patterns (e.g., triangles, paths) in temporal proximity graphs using an implicit spatial-embedding + time-interval node representation. Also supports interactive durability-threshold queries via incremental updates computed in time near-linear in the size of result changes, leveraging proximity structure to outperform prior super-linear, non-guaranteed methods. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pankaj K. Agarwal (Duke University)
- 2. Xiao Hu (University of Waterloo)
- 3. Stavros Sintos (University of Illinois Chicago)
- 4. Jun Yang (Duke University)
BibTeX Citation
@inproceedings{agarwal_pods24,
address = {New York, NY, USA},
series = {{PODS} '24},
title = {{On Reporting Durable Patterns in Temporal Proximity Graphs}},
url = {https://dl.acm.org/doi/10.1145/3651144},
doi = {10.1145/3651144},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Agarwal, Pankaj K. and Hu, Xiao and Sintos, Stavros and Yang, Jun},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,467 | Output-sensitive Conjunctive Query Evaluation | 2024 | PODS | 5.7747248e-05 |
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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 |
|---|---|---|---|---|
| 315 | Worst-Case Optimal Join Algorithms: Techniques, Results, and Open Problems | 2018 | PODS | 0.00021246 |
| 637 | Answering Conjunctive Queries under Updates | 2017 | PODS | 0.00015341557 |
| 812 | The Dynamic Yannakakis Algorithm: Compact and Efficient Query Processing Under Updates | 2017 | SIGMOD | 0.00013729015 |
| 6,738 | Efficiently Answering Durability Prediction Queries | 2021 | SIGMOD | 5.6918011e-05 |
| 7,609 | Computing Complex Temporal Join Queries Efficiently | 2022 | SIGMOD | 5.4847975e-05 |
| 7,957 | Better Sliding Window Algorithms to Maximize Subadditive and Diversity Objectives | 2019 | PODS | 5.4183555e-05 |
| 12,252 | Durable Top-k Queries on Temporal Data | 2018 | VLDB | 4.9793485e-05 |
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