Approximately Counting Triangles in Large Graph Streams Including Edge Duplicates with a Fixed Memory Usage
Summary: One-pass streaming algorithm uniformly samples distinct edges from large graph streams with duplicates, achieving O(1) per-edge sampling and no extra memory. It infers triangle counts from samples, outperforming prior methods in accuracy and speed within the same memory footprint. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pinghui Wang
- 2. Yiyan Qi
- 3. Yu Sun
- 4. Xiangliang Zhang
- 5. Jing Tao
- 6. Xiaohong Guan
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,067 | Sliding Window-based Approximate Triangle Counting over Streaming Graphs with Duplicate Edges | 2021 | SIGMOD | 7.6247945e-05 |
| 5,529 | Hypergraph Motifs: Concepts, Algorithms, and Discoveries | 2020 | VLDB | 5.4569473e-05 |
| 7,800 | Triangular Stability Maximization by Influence Spread over Social Networks | 2023 | VLDB | 4.6437574e-05 |
| 8,172 | LM-SRPQ: Efficiently Answering Regular Path Query in Streaming Graphs | 2024 | VLDB | 4.5653572e-05 |
| 10,495 | Finding Logic Bugs in Graph-processing Systems via Graph-cutting | 2025 | SIGMOD | 4.1905499e-05 |
| 10,594 | GREAT: Generalized Reservoir Sampling based Triangle Counting Estimation over Streaming Graphs | 2025 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 389 | Counting Triangles in Data Streams | 2006 | PODS | 0.00024649634 |
| 588 | Massive Graph Triangulation | 2013 | SIGMOD | 0.00019588834 |
| 1,348 | Counting and Sampling Triangles from a Graph Stream | 2013 | VLDB | 0.00012461666 |
| 2,219 | The Input/Output Complexity of Triangle Enumeration | 2014 | PODS | 9.2653868e-05 |
| 2,811 | All-Distances Sketches, Revisited: HIP Estimators for Massive Graphs Analysis | 2014 | PODS | 8.0840418e-05 |
| 3,537 | OPT: A New Framework for Overlapped and Parallel Triangulation in Large-scale Graphs | 2014 | SIGMOD | 6.9929946e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,532 | How the Degeneracy Helps for Triangle Counting in Graph Streams | 2020 | PODS | 4.4893996e-05 |
| 9,231 | Efficiently Counting Triangles in Large Temporal Graphs | 2025 | SIGMOD | 4.3648789e-05 |
| 11,323 | Approximately Counting Subgraphs in Data Streams | 2022 | PODS | 4.1905499e-05 |
| 4,903 | On Sampling from Massive Graph Streams | 2017 | VLDB | 5.8403259e-05 |
| 10,123 | Triangle Counting in Hypergraph Streams: A Complete and Practical Approach | 2026 | SIGMOD | 4.1905499e-05 |
| 10,594 | GREAT: Generalized Reservoir Sampling based Triangle Counting Estimation over Streaming Graphs | 2025 | VLDB | 4.1905499e-05 |
| 1,348 | Counting and Sampling Triangles from a Graph Stream | 2013 | VLDB | 0.00012461666 |
| 5,043 | Better Algorithms for Counting Triangles in Data Streams | 2016 | PODS | 5.7350154e-05 |
| 3,067 | Sliding Window-based Approximate Triangle Counting over Streaming Graphs with Duplicate Edges | 2021 | SIGMOD | 7.6247945e-05 |
| 389 | Counting Triangles in Data Streams | 2006 | PODS | 0.00024649634 |