OPT: A New Framework for Overlapped and Parallel Triangulation in Large-scale Graphs
Summary: OPT is a disk-based, overlapped, parallel triangulation framework for billion-scale graphs, achieving near-ideal cost by CPU–I/O overlap. It uses internal/external triangles, macro/micro overlaps, and vertex- and edge-iterator models, with linear speedups. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jinha Kim
- 2. Wook-Shin Han
- 3. Sangyeon Lee
- 4. Kyungyeol Park
- 5. Hwanjo Yu
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,529 | Truss-based Community Search: a Truss-equivalence Based Indexing Approach | 2017 | VLDB | 0.00011484853 |
| 2,799 | DUALSIM: Parallel Subgraph Enumeration in a Massive Graph on a Single Machine | 2016 | SIGMOD | 8.109137e-05 |
| 3,067 | Sliding Window-based Approximate Triangle Counting over Streaming Graphs with Duplicate Edges | 2021 | SIGMOD | 7.6247945e-05 |
| 4,801 | Ringo: Interactive Graph Analytics on Big-Memory Machines | 2015 | SIGMOD | 5.906922e-05 |
| 4,883 | Approximately Counting Triangles in Large Graph Streams Including Edge Duplicates with a Fixed Memory Usage | 2018 | VLDB | 5.8519327e-05 |
| 5,529 | Hypergraph Motifs: Concepts, Algorithms, and Discoveries | 2020 | VLDB | 5.4569473e-05 |
| 8,538 | On Asymptotic Cost of Triangle Listing in Random Graphs | 2017 | PODS | 4.4893996e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 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 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 12,049 | I/O Efficient: Computing SCCs in Massive Graphs | 2013 | SIGMOD | 4.1905499e-05 |
| 9,088 | Efficiently Enumerating Minimal Triangulations | 2017 | PODS | 4.3940132e-05 |
| 5,014 | TurboGraph++: A Scalable and Fast Graph Analytics System | 2018 | SIGMOD | 5.7519428e-05 |
| 389 | Counting Triangles in Data Streams | 2006 | PODS | 0.00024649634 |
| 9,070 | GraphTwist: Fast Iterative Graph Computation with Two-tier Optimizations | 2015 | VLDB | 4.3982218e-05 |
| 3,976 | Accelerating Truss Decomposition on Heterogeneous Processors | 2020 | VLDB | 6.5694893e-05 |
| 5,043 | Better Algorithms for Counting Triangles in Data Streams | 2016 | PODS | 5.7350154e-05 |
| 110 | On Triangulation-based Dense Neighborhood Graph Discovery | 2011 | VLDB | 0.00047955011 |
| 4,146 | Accelerating Triangle Counting on GPU | 2021 | SIGMOD | 6.4065776e-05 |
| 588 | Massive Graph Triangulation | 2013 | SIGMOD | 0.00019588834 |