BOOMER: Blending Visual Formulation and Processing of P-Homomorphic Queries on Large Networks
Summary: Boomer blends visual, interactive formulation of bounded 1-1 p-hom queries with online processing via a novel cap index. Cap index supports immediate and deferment-based construction, enabling interleaved refinement and processing; experiments on real networks show efficiency. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yinglong Song
- 2. Huey Eng Chua
- 3. Sourav S Bhowmick
- 4. Byron Choi
- 5. Shuigeng Zhou
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,906 | In-Memory Subgraph Matching: An In-depth Study | 2020 | SIGMOD | 0.00010135267 |
| 8,488 | A Framework for Privacy Preserving Localized Graph Pattern Query Processing | 2023 | SIGMOD | 4.4951247e-05 |
| 10,740 | Subgraph Matching: A New Decomposition Based Approach | 2025 | VLDB | 4.1905499e-05 |
| 10,852 | Efficient Top-k Frequent Subgraph Mining Using Tight Upper and Lower Bounds | 2025 | VLDB | 4.1905499e-05 |
| 11,582 | BOOMER: A Tool for Blending Visual P-Homomorphic Queries on Large Networks | 2020 | SIGMOD | 4.1905499e-05 |
| 11,664 | Answering Why-questions by Exemplars in Attributed Graphs | 2019 | SIGMOD | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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